Stem cell reserch Essay Example For Students

Undifferentiated cell reserch Essay #65279; Science is moving at such a fast speed nowadays, between cloning, quality treatment, supernatural occurrence drugs, extraordinary treatments, and so on. One of the most critical advancements came in November 1998, when two separate analysts effectively confined stem cells from human undeveloped organisms and prematurely ended babies. Undifferentiated cells are early stage cells of a human creature, which are equipped for turning into all or a large portion of the 210 various types of tissues in the human body. Foundational microorganisms have been characterized as not completely separated however to be a specific kind of tissue or cell. They extend from totipotent, I. e. ( the beginning times of the human undeveloped organism up to around 4 days after origination.) To pluripotent For example (somewhat more established and in this way just equipped for being a few cells or tissues in the body.) As in the 5-multi day blastocyst phase of the early incipient organism, with diminishing limit in later phases of fetal turn of events and in people. The ardent expectations are that these foundational microorganisms can be utilized to incredible points of interest. The careful feelings of dread are that guiltless and powerless people are decimated, and unnecessarily in this way, all the while. The discussions are seething. Numerous individuals are befuddled about what foundational microorganism inquire about truly is, and wonder why all the whine. There are a few all around reported and well- verbalized wellsprings of data accessible on this issue as of now, so coming up next is a brief review of a portion of the major logical, moral, upsides and downsides. For a considerable length of time mankind has been tormented with various sicknesses, for example, the dark plague, Cancer, AIDS, and different infections. These awful, feared ailments have slaughtered a large number of individuals because of specialists or researchers not having a fix, yet thanks to a logical and clinical advancement these infections can and will be a thing of the past. With this new research researchers are wanting to increase significant logical information about early stage advancement and its application to related fields; relieving incapacitating illnesses, e.g., Parkinsons, Alzheimers, diabetes, stroke, spinal string wounds, bone ailments, and so forth.; and screening drugs for pharmaceutical organizations, rather than depending on creature models. So as to proceed with these clinical and logical advancements you need to acknowledge the right-to-life contention in its most extraordinary structure. Im discussing recently shaped undeveloped organisms. These are not babies with small waving hands and feet. These are minute groupings of a couple of separated cells. There is nothing human about them, aside from potential, and just on the off chance that you decide to trust it, a spirit. In any case, Bush is blocking, undifferentiated cell research would not really end the life of a solitary undeveloped organism. Scientists would just utilize undeveloped organisms that are being disposed of at any rate. 1 I comprehend that a few people and master lifers state that undifferentiated cell inquire about is murder. In any case, I emphatically fell that it is morally satisfactory even ethically required to obliterate a couple of people so as to potentially profit a huge number of patients. In addition, these cells don't cause the equivalent immuno-contrariness issues after transplantation as do grown-up undifferentiated cells from various patients. Further, these early cells from human incipient organisms and embryos are MORE totipotent and pluripotent than grown-up undeveloped cells, and in this manner they can be cajoled to turn out to be increasingly various types of tissues, and can last longer in culture anticipating use. In addition, these embryos and left- over IVF-created human incipient organisms are going to bite the dust in any case, so we should get some great use out of them.1 Researchers accept that immature microorganisms can impersonate the activities and exercises of about each other cell in the body. In the end, researchers plan to utilize them to fix harmed hearts after coronary failures, recover livers crushed by cirrhosis or viral sickness, reproduce harmed joints, or seed the mind with new neurons to switch the impacts of Parkinsons what's more, Lou Gehrigs malady, as per the November issue of Technology Audit, an exploration magazine distributed by the Massachusetts Institute of Innovation, or MIT. 2 Presently for each great there is an awful, and with this innovation there must be a negative side, after all everything with drug and clinical research has its side impacts, and a large number of individuals on the planet feel that foundational microorganism look into is ethically what's more, morally wrong paying little heed to what foundational microorganism explore guarantees, just as all the symptoms that join undifferentiated organism investigate. Here are only a portion of the side impacts or things that aren't right or exploitative. Initial, one minor inconvenience is that utilization of human early stage immature microorganisms requires long lasting utilization of medications to .

Four Things I Learned While Writing Crime Fiction

Four Things I Learned While Writing Crime Fiction Four Things I Learned While Writing Crime Fiction After a visit in Iraq, which made them lead security for EOD missions, flexibly runs, and whatever else the military asked of him, Zack Klika got out and headed off to college at The University of Texas Dallas. He graduated in 2010 with a B.S. in Finance. It was around this time he concluded that composing was what he truly needed to do, not numbers. In this article, he discusses the four greatest suggestions he found out about composing wrongdoing fiction by working with proficient editors. My new novel, Blood On The Bridge, is around three totally different individuals banding together to make sense of who killed a female fighter. Furthermore, much like the characters in my book, I collaborated with two astounding editors, Will Anderson, my formative manager, and Mary Beth Constant, my duplicate supervisor, to get my novel fit as a fiddle. Composing a novel is no simple assignment. I delineated for a month and afterward composed the primary draft in two, so, all things considered I realized I expected to get experts included. Will had such a significant number of incredible remarks and recommendations about my original copy that it empowered me when the opportunity arrived to jump back in for a revise. Mary Beth detected a large number of irregularities in my story’s course of events and by and large story curve. Without her, the novel would have put on a show of being unprofessional. The two of them restored my alters before the due date we had settled upon too, which caused me to feel considerably progressively positive about the Reedsy platform.Here is a portion of the counsel I got during the composition and altering process, in regards to making an extraordinary spine chiller novel.1) Embrace the tropesThere is literally nothing amiss with feeling like your riddle or spine chiller rings like a ton of other wrongdoing fiction. Be that as it may, there are approaches to cause your scene to feel more unique than it truly is. The best bit of specialty exhortation I at any point got really wasn’t identified with composing. It was given to me during a comedy class. My educator advised the gathering to discard the initial three thoughts that flew into our heads when we strolled onto the phase to play out a scene. Furthermore, it generally worked. It powers your creative mind to scramble for something that wasn’t as of now there. Furthermore, when you’re confronted with no chance to get out, you will discover an exit plan. It’s how a ton of authors compose: they get themselves into trouble and afterward discover an exit plan. At the point when you're composing type fiction, don't be hesitant to grasp the tropes There is a scene in my novel where one of the principle characters is taken out and tossed into the storage compartment of a vehicle. He awakens in the storage compartment and acknowledges he is being headed to his demise bed. Anyway, what would he be able to do when his hijackers open the storage compartment? Battle or flight? Those are two choices. He could likewise ask. Those were actually the main three alternatives I could consider. Afterward, when I was laying in bed attempting to rest, a fourth alternative came to me: he could feign unconsciousness. Furthermore, I’m sure I’m not by any means the only one to ever expound on a character feigning unconsciousness in the storage compartment of a vehicle while in transit to his strict passing bed. However, paying little mind to how utilized of a figure of speech it will be, it was the alternative that totally fit my character best and not simply the principal thing I could think of.Don’t neglect to depend on you r formative editorial manager as a hotspot for extraordinary thoughts which drives me to the following part...2) Run with your editor’s adviceSeriously. Take their thoughts, counsel, and criticism and go for it. They’ve most likely read significantly more wrongdoing fiction than you ever will so they are the ideal individual to reveal to you how to make your book better.Authors will in general get exclusive focus while they’re taking a shot at their original copy. Make an effort not to be vexed if your formative supervisor reveals to you the person doesn’t feel like a scene works in its present state. The fundamental occupation of that manager is to investigate your work. On the off chance that they’re incredible editors, as were mine, they’ll toss out a plans to improve the scene. Consider those thoughts and use them as you see fit. The spine chiller composing exercises I learned by working experts editors I realized something was absent from my book when I submitted it to Will. I couldn’t put my finger on it, however Will thought that it was immediately: I required another distraction in my story. There wasn’t enough going on in the subsequent demonstration to support it all the way to the finish. One of the thoughts Will gave me was great and directly before my eyes the entire time. I went for it. What's more, it wound up making my story even more charming. Also, you need to be engaged by your novel.Want to get familiar with comfortable wrongdoing fiction - and get some suggested titles while you're busy? Look at thisâ comprehensive manual for comfortable mysteries.3) Use your sensesIf you’re not engaged by your wrongdoing fiction, your peruser won’t be either. I compose secrets and spine chillers since I have an enthusiasm to engage and I’ve consistently been engaged by a decent wrongdoing story. Recollect that your spine chiller or puzzle is bein g advised to somebody, and they should be brought into your pretend world. The most ideal approach to do that is through appear, don't tell and by joining every one of the five faculties into your composition: sight, sound, smell, taste, touch.After a first or second draft, I’ll experience my original copy and see which of the five faculties are deficient. Sight and sound get utilized the most in a ton of composing, which is splendidly fine. Be that as it may, smell, taste, and contact can be your sleuth’s/detective’s closest companion and can represent the deciding moment a case. Did your investigator get a whiff of cologne off the killed lady found in her loft? Did he later smell that equivalent cologne while meeting a suspect? An incredible exercise I like to do is to work out a couple of ways an executioner can be gotten based off one of those three detects. It’s difficult, however that just methods your story will be all the better for it. My next su ggestion will improve your story as well. The four best suggestions I learned while composing wrongdoing fiction 4) Keep your activity scenes free and free-flowingDon’t get excessively hindered in being so exact with the subtleties that your peruser can’t fill in certain spaces for themselves and inundate themselves in the story. In the event that you’re composing inside the domain of reality it might be a smart thought to keep your battles on the shorter side also, to assemble tension. Genuine battles are not at all like fights. Genuine battles are untidy. Genuine battles are normally wrapped up inside a couple of moments. Also, genuine warriors battle grimy. Recall that. Your contenders don’t keep any standards. They will do whatever they need to do to win a fight.Please share your contemplations, encounters, or any inquiries for Zack Klika in the remarks underneath! What's more, in the event that you'd prefer to get familiar with questioning a spine chiller to a specialist, head here.Blood on the Bridge is accessible in soft cover and on Amazon Kindle!

Tweet, tweet

Tweet, tweet I know its been forever since Ive posted anything things have been so crazy busy, I dont ever seem to have time to sit down and blog anymore! But now that I finally got a smartphone last month (I 3 my Droid X), Ive been finding myself using Twitter a lot more. So if youre interested, feel free to follow me Im @MikeyMIT. Meanwhile, Ive been coming across all these really cool stories of MIT in the news that Ill try to post (or more likely, tweet) to share with you all. Today, this mention of MIT was on CNN.com: http://www.cnn.com/2010/TECH/innovation/08/26/mit.oil.robot/ And a few days ago, this article from Gizmag about work being done on batteries (designed by viruses!) that can be woven into clothing: http://www.gizmag.com/mit-developing-werable-batteries/16110/ Some pretty cool research and development being done its stuff like this that makes me so proud (and in awe) to be associated with MIT. :) As the new school year begins (and 14s are arriving this week and next!), Im looking forward to yet another interesting year. In my plans for upcoming posts, Im hoping to talk a little more specifically about my particular role in the Admissions Office, and some college-admissions-related issues near and dear to my heart. (And perhaps an obligatory what I did this summer post) Meanwhile, as the summer comes to an end, how was your summer? Do anything fun/interesting/cool?

Health Insurance Matrix - 3133 Words

University of Phoenix Material Health Insurance Matrix As you learn about health care delivery in the United States, it is important to understand the various models of health insurance to develop a working knowledge as you progress through the course. The following matrix is designed to help you develop that knowledge and assist you in understanding how health care is financed and how health insurance influences patients and providers as important foundational information for your role as a future health care worker. Fill in the following matrix. Each box must contain responses between 50 and 100 words using complete sentences. Include APA citations for the content you provide. Origin: When was the model first used? What kind of†¦show more content†¦Indemnity health plans run on a retrospective payment system. A member has a monthly premium. Co-pays and a deductible. Upon visits the provider submits claims for services rendered to the insurance company, upon which the insurance company pays their part and the member is billed for the remaining balance to be paid out-of-pocket. With indemnity plans employers deduct the monthly premium from payroll of each employee on the plan. Both the member and the insurance company pay for services rendered. Upon receipt of the services the insurer pays the provider their portion if the deductible has been met. The member is then responsible for the remaining balance and the co-pay at the time of service. The structure of an indemnity plan is completely â€Å"open access†. The member may choose any provider or specialist they would like. In an indemnity plan there are no restrictions on providers or provider type. It is the member’s responsibility to seek and sign on with their preferred provider or specialist. Positive aspects of indemnity plans include the liberty of the member to choose their preferred provider or specialist and their preference of type of care they wish to receive. A negative aspect of indemnity plans from a members stand point is the cost of these plans. Premiums and deductibles then to be higher with indemnity plans over other insurance plans due to the freedomShow MoreRelatedHealth Insurance Matrix Essay2138 Words   |  9 Pagesï » ¿ University of Phoenix Material Health Insurance Matrix Origin: When was the model first used? What kind of payment system is used, such as prospective, retrospective, or concurrent? Who pays for care? What is the access structure, such as gatekeeper, open-access, and so forth? How does the model affect patients? Include pros and cons. How does the model affect providers? Include pros and cons. Indemnity In 1932 the American Medical Association (AMA) adopted a strong positionRead Morehealth insurance matrix HCS/235 Essay637 Words   |  3 PagesMaterial Health Insurance Matrix As you learn about health care delivery in the United States, it is important to understand the various models of health insurance to develop a working knowledge as you progress through the course. The following matrix is designed to help you develop that knowledge and assist you in understanding how health care is financed and how health insurance influences patients and providers as important foundational information for your role as a future health care workerRead More HCS 235 Week 2 Completed Health insurance matrix1163 Words   |  5 PagesMaterial Health Insurance Matrix As you learn about health care delivery in the United States, it is important to understand the various models of health insurance to develop a working knowledge as you progress through the course. The following matrix is designed to help you develop that knowledge and assist you in understanding how health care is financed and how health insurance influences patients and providers as important foundational information for your role as a future health care workerRead MoreHistorical Context Matrix Essay1588 Words   |  7 PagesUniversity of Phoenix Material Historical Context Matrix As you learn about health care delivery in the United States, it is important to understand the history of health care delivery to develop a working knowledge as you progress through the course. The following matrix is designed to help you develop that working knowledge. Fill in the following matrix. Each box should contain responses between 50 and 100 words. |Historical Context |Historical background?|Where is the care |WhoRead MoreHCS/212 Health Services and Systems Matrix Essay1227 Words   |  5 Pagesï » ¿University of Phoenix Material Health Services and Systems Matrix Choose at least seven services or systems from the following list: Hospice care World Health Organization (WHO) Public health Rehabilitation center Department of Health and Human Services (DHHS) Medicare Centers for Medicare and Medicaid Services (CMS Center for Disease Control (CDC) Health Maintenance Organization (HMO) Occupational Safety and Health Administration (OSHA) Joint Commission on Accreditation of HealthcareRead MoreManage Care and How It Has Affected and Changed Health Care Essay1161 Words   |  5 PagesCare and How It Has Affected and Changed Health Care Manage Care and how it has affected and changed Health Care â€Å"Managed care embodies an effort by employers, the insurance industry, and some elements of the medical profession to establish priorities and decide who gets what from the health care system.† (JAMA.2001; pg. 285:2622-2628). Manage Care is part of the Health Care system since 1973 is known as the system that finances and delivers health care to individuals enrolled under theirRead MoreFinancing The Failing U.s. Healthcare System1515 Words   |  7 Pagesservice, fee-for-service. Variable payment reimbursement removes the burden of risk from the health care providers because they needn’t worry about the costs of their services exceeding the fixed amounts they receive. The amount a consumer is forced to pay determines to what degree they are incentivized to utilize healthcare services from providers. Little to no out-of-pocket costs and a high level of insurance coverage act as an incentive for a consumer to seek medical services while a consumer withRead MoreEssay about MATRIX GRID hcs 455 week 2 2464 Words   |  10 Pagesï » ¿University of Phoenix Material Health Care Reform Matrix With your learning team, complete the Health Care Reform matrix below. Listed in this matrix are some of the topics addressed by the Patient Protection and Affordable Care Act policy. You are required to describe the issue, in your own words, and list 2-3 points about each topic under each heading in the matrix. Describe the issue: Key concerns regarding the issue: How is this issue addressed in the current health care environment? How will thisRead MoreReadiness for Future Health Needs at Banner Health1249 Words   |  5 Pagesï » ¿Readiness for Future Health Needs at Banner Health Name Grand Canyon University Michael Jones NRS- 451V Date Readiness for Future Health Needs at Banner Health Banner Health celebrates its fifteen year anniversary this year (2014). Samaritan Health System merged with Lutheran Health System September 1st, 1999. Lutheran Health System began in 1938 across Western and Mid-Western states. Samaritan Health System dates back to 1911 that covered California and Arizona, primarilyRead MoreThe Shift Of The Affordable Care Act ( Aca )1100 Words   |  5 Pagesof different payment and reimbursement options, health insurance programs, and the establishment of the Affordable Care Act (ACA). Between May 2009 and April 2012, one of the initial PCMH pilot programs was conducted in Colorado, appropriately named The Colorado Multipayer Patient-Centered Medical Home Pilot. More than 100,000 patients within sixteen internal medicine practices participated in the experimental PCMH model, using six different health plans (Harbrecht Latts, 2012). When the pilot

The Importance Of A School Average Scores - 1201 Words

Helen Keller once said â€Å",character cannot be developed in ease and quiet. Only through experience of trial and suffering can the soul be strengthened, ambition inspired, and success achieved.† This quote indicates how a school average scores can be below average, but if the student s and teacher’s work together they will succeed. The problem could be students might not make effort, teachers might not have the right resources to teach students, personal problems might stop students from succeeding, or the school in general might need guidance academically. Additionally, students might not be fantastic test takers in general. Though test scores show schools’ improvement, students can’t be forced to increase scores. However, to close school some think consistently low scores mean it s time. For example, school boards, state officials, the State Department of Education might take scores under consideration. There is no guarantee that score averages wil l increase as a whole. There are several types of students and some just are careless, don’t take school serious, or don’t bother to attend school to receive the knowledge that s needed. Students might be careless by not studying, not being prepared, or not paying attention period. Nevertheless, students might not take school serious because his or her family members might no push education. This would give the student a reason not to come to school to receive the lesson to succeed. Some schools’ suffer lack of funds, orShow MoreRelatedAnalysis Of Addison s Essay775 Words   |  4 PagesBackground Information Family History Addison is a third grade student at Westside Elementary School in the West Fargo Pubic School District. Addison is nine years old. Addison’s is the oldest child in her family. She has a five year old brother and an eighth month old brother. Addison’s mother feels that Addison is not a proficient reader. She feels that Addison is a slower reader. Addison’s mother stated Addison sometimes struggles with longer word and can’t keep the flow of the sentenceRead MoreThe Center For Disease Control ( Cdc ) And The World Health Organization1287 Words   |  6 Pagesbridging the achievement gap between students and less emphasis has been placed on non-academic curriculum such as, physical education. Research has shown that approximately 3.8% of elementary schools provide formal physical education with this percentage steadily declining as children continue onto middle and high school. This decrease in physical activity is in line with reports from the CDC which estimate that one third of children in the United States are overweight and, within those cases, the CDCRead MoreShould Kids Be Kids?992 Words   |  4 Pagesstandardize test given to all students. The No Child left behind act has set yearly stand ards for the competence of the schools through an adequate yearly progress score. 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This decrease in physical activity is in line with reports from the CDC which estimate that one third of children in the Uni ted States are overweight and, within those cases, the CDCRead MoreAddison s Attitude Towards Reading816 Words   |  4 PagesFamily History Addison is a third grade student at Westside Elementary School in the West Fargo Pubic School District. Addison is nine years old. Addison lives with her parents and two younger brothers. Addison’s mother stated Addison is not a proficient reader. She feels that Addison reads slowly. Addison’s mother stated Addison struggles with longer words and struggles to keep the flow of the sentence, but acknowledges Addison’s comprehension is a strength when mom reads with her. Addison becomesRead MoreWhy Americas Educational System is Failing1123 Words   |  5 PagesStandardized Exam Cheating in 37 States And D.C., New Report Shows Widespread Test Score Corruption†). 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As more and more distractions are made available to the American teenager, it is imperative that today’s students are aware of the importance of doing theirRead MorePrivate Or Public School?1321 Words   |  6 Pages Private or Public School? Adrianna N. Pillow Professor SooHoo-Hui February 15, 2015 California Baptist University â€Æ' Abstract In today’s society, receiving a good education has become of the utter most importance. The real choice that is being faced now is what type of schooling program kids should be sent to. Should it be private school, with smaller class sizes or public school, where the massive attendance count tends to make kids learning last on the lists of priorities? The obvious choiceRead MoreThe University School Of Medicine868 Words   |  4 PagesTulane University School of Medicine is located in New Orleans, Louisiana and was founded in 1834. The medical school is the second oldest medical school in the Deep South and is the fifteenth oldest medical school in the country. Tulane only selects the most well qualified students into their medical program. Each year, approximately ten thousand prospective students submit applications to the university with only about 500 receiving an invitation for an interview. form those 500, 212 will beRead MoreAre Standardized Tests a Good Measure of Ones Ability? Essay1146 Words   |  5 Pagesphase of having to take a standardized test to apply for a college, a scholarship program or better still to complete the high school program. Normally good scores in these tests guarantees good scholarships or admission into an institution because the scores from standardize tests are used as a conclusive measure of one’s abilities. But due to the fact that these scores ignores years of hard work and commitment and focuses on just a test, it’s about time we acknowledge standardized tests are not

How I Met Myself Free Essays

string(43) " cold January evening when he met himself\." How I Met Myself Q: Based on the novel above, describe the main character. Answer with evidence. Ans: The main character in the novel ‘How I Met Myself‘ is John Taylor. We will write a custom essay sample on How I Met Myself or any similar topic only for you Order Now He is a 34-year-old-Englishman living and working in Hungary. He is 2 meters tall with light brown hair and eyes and a moustache. Taylor is adventurous and eager to try something new. He is a computer programmer who takes a job in another country, especially in one which he has never visited before, because he thinks it will be interesting. He takes Hungarian lessons from a girl named Andrea. They fall in love and get married. Later, they also have a daughter whom they name Kati. Taylor is also curious and determined to understand the strange meeting that took place on 18 January. He feels afraid whenever he thinks of the strange encounter but his curiosity pushes him to seek answers. Q : Based on the novel above, describe one of the following moments in the story, answer with evidence. – the most frightening – the saddest Ans : The most frightening part in the novel ‘How I Met Myself’ is when the main character, John Taylor meets himself. The incident happens one evening when a man comes out of a street door and runs straight into Taylor. It is eerie that when the man apologises and Taylor looks at his face, he sees someone who looks just like him. He has the same features as Taylor. Even more puzzling as well as intriguing is that there are no footprints on the snow left by the man. Taylor follows the man but discovers no one has seen him. He seems to have simply vanished. Taylor’s life changes after that strange encounter as he begins to have dreams about the meeting. It is frightening because he has to relieve the experience over and over again. He also always wakes up feeling afraid. Taylor cannot understand the meaning of the strange meeting which only makes it intriguing. Q : Based on the novel above, describe an important event which changes the main character’s life, answer with evidence. Ans : In the novel ‘How I Met Myself’ the life—changing event for John Taylor is when he meets himself during one cold January evening, A man runs into Taylor and he looks just like him. The strange meeting is both confusing and frightening for Taylor. Taylor’s life changes after the strange event. He dreams about the encounter every night. He gets up in the dark feeling afraid every night. At times, when he does not go back to sleep after dreaming, he lays awake. He grows more and more tired. He even isn’t nice to his wife, Andrea. He also isn’t honest with her. He does not tell her that he is arriving home late every night. Andrea also notices the change in his attitude and she is unhappy, Even his work life is affected. He finds it difficult to think about the things he has to do. Soon, Taylor is afraid to go home and sleep because he is afraid he will dream the same dream. He no longer has a simple and happy life with his wife like he did before the strange meeting. Q : Based on the novel above, describe the relationship between two characters, answer with evidence. Ans: In the novel ‘How I Met Myself’, the two characters I would like to write about are John Taylor and his wife, Andrea. Taylor and his wife share a close and loving relationship. Andrea notices a change in her husband’s attitude. She feels hurt and upset. Taylor loves Andrea very much and fees terrible that he has been hurting her. At first, Taylor does not tell his wife about his strange meeting and his recurring dreams. However, when he does, she wants to help him find answers to his questions about the strange encounter. Taylor soon begins to feel more hopeful for the future once Andrea knows the truth. They work together to find information about the man’s identity. Even though, they learn nothing from talking to the people living in the buildings where the strange meeting took place, the fact that Andrea knows about the strange meeting is comforting to Taylor. His life returns to what it was before. Soon, they discover they will have a baby. Q : Based on the novel above, write about a conflict between the characters, answer with evidence. Ans: In the novel ‘How l Met Myself’ conflict arises between Taylor and his wife, Andrea, because of the strange events that happened to Taylor that turned his life upside down. Andrea is first unhappy with Taylor’s change in attitude. Once she knows what is troubling him, she helps to investigate. However, Taylor continues to dream about the strange meeting and wants to know the truth. In doing so, he spends less time with Andrea and his daughter He also does not tell her that he goes to the ibrary to read old newspapers to find clues that can help him make sense of his strange meeting. When she finds out, she is angry and does not want to help him anymore. Andrea fails to understand that her husband wants to be free of the dreams. The story of the doppelganger may seem impossible in the normal world so she finds it hard to believe her husband. She grows tired of hi s doppelganger story and wants him to think about taking care of his family. The doppelganger and Taylor’s quest to find answers seem to drive a wedge between Taylor and Andrea. Later, she even thinks he is ill and needs a doctor’s help. Q: Based on the novel above, write about an important event/s in one of the character’s life, answer with evidence. Ans: In the novel ‘How l Met Myself’ the most important event occurs when John Taylor discovers more about what happened to him one cold January evening when he met himself. You read "How I Met Myself" in category "Papers" It is called a doppelganger. Taylor realizes that he had met his doppelganger that evening. Then, after talking to his old friend, he realizes he is not crazy and what happened to him has happened to other people. His friend tells him that a doppelganger comes to give a message to the person who can see him. After New Year, Taylor realizes that the one year anniversary of the strange meeting is drawing near. Then, an idea comes to him. He realizes that the date is important. This is the reason he has never met himself again after the first meeting. Taylor begins to investigate all the events that took place on that day in the past. He looks at some old newspapers to find out if there was any event that could help him understand what is happening to him. These separate events which occurred after the first strange meeting were important to help Taylor understand, at least a little, what he experienced. Q: Based on the novel above, write about a quality which you like in a character, answer with evidence. Ans : In the novel ‘How l Met Myself’ I like the determination shown by John Taylor. Even though the strange meeting is puzzling and he is afraid about what he is experiencing, he wants to learn more about it. He does not know what frightening revelation may be in store if he uncovers the truth but it is better than doing nothing. He does some research like reading old newspapers and with his wife talks to people near the location of the strange meeting to find out the identity of the man. He also confides in his old friend about his experience. All along, after the first strange meeting, he still has dreams about the encounter which leaves him afraid to sleep and more and more tired. His life is turned upside down with a few happy moments such as the birth of his first child. However, the dreams come back to haunt him. Taylor’s determination to seek the truth probably helped him maintain his sanity and peace of mind. Q: Based on the novel above, write about your favourite part in the novel, why do you like this part? Answer with evidence. Ans: My favourite part in the novel ‘How I Met Myself is when Taylor finds relevant information that can help him understand what happened to him. He reads about a story where a woman and a child died in a cellar of a building in Gergely utca which was hit by a Russian bomb. The tragedy occurred on 18 January which was the same date that Taylor met himself. The doppelganger comes out of a building in Felka utca and runs to Gergely utca. This part is interesting because this information also sheds some light on Taylor‘s doppelganger. Taylor talks to several people to enquire about the name Szabo. An old woman tells Taylor about Janos Szabo and the tragedy which befell his wife and daughter. There are several similarities between Taylor and Janos Szabo. It is at this time that Taylor realizes his doppelganger wants to help him but he is still puzzled why he appears to look like him. I like this part as it gives me clues to solve the mystery surrounding the doppelganger. I realize that Taylor’s wife, Andrea, and his daughter are in danger. Q: Based on the novel above, do you like the ending of the novel? Answer with evidence. Ans: I like the ending in the novel ‘How l Met Myself’. This is mainly because it has a happy ending. The story reaches a suspenseful moment when Taylor realizes that Janos Szabo is Hungarian for John Taylor. Taylor and his doppelganger share the same. Then, he discovers that Janos Szabo‘s wife and daughter were also named Andrea and Kati respectively. Then, on 18 January. Andrea leaves a note saying that she and Kati will be at the bar. Taylor runs to get them but there is a blast. Taylor arrives at the bar and frantically tries to clear the entrance. However, he is told to go home so the authorities can clear the debris. Taylor feels terrible that he was too interested in the doppelganger and not on what he wanted to tell him. He thinks his life is destroyed and that he will never be happy again without his wife and daughter. I feel terrible for Taylor, too, because he could not save his family. Unexpectedly the doppelganger appears to him again and points to Andrea and Kati. Taylor is so happy. The ending is happy and bittersweet too because Szabo, unable to save his own wife and daughter, in the end helped to save Taylor’s wife and daughter. Q: Based on the novel above, write about an unexpected twist in the story, answer with evidence. Ans: In the novel ‘How l Met Myself’ an unexpected twist comes towards the end of the story when the doppelganger appears to someone close to Taylor to give that person an important message. He wants to save Andrea and Kati’s lives because Taylor has not been able to understand or act upon the earlier warnings. After the blast, Taylor walks home, thinking that his wife and daughter have just died in the cafe. Suddenly, he bumps into his doppelganger. The doppelganger points to Andrea and Kati. Taylor is so happy to be reunited with his family. On three previous occasions, the doppelganger appears to Taylor as he (the doppelganger) runs out of Felka utca. He, then, appears in front of Andrea and Kati to warn them. Andrea thinks John is blocking their way but when Kati begins to cry she realizes that it is his doppelganger. He wants them to leave the place so they do. Janos Szabo enters Taylor and his family’s life to save them. He lost his family too and probably does not want someone else to suffer like he did. Q: Based on the novel above, write about an interesting character that you admire. Answer with evidence. Ans: An interesting character that l admire is Andrea Taylor from the novel How I Met Myself. She is a loving and understanding wife. She always puts her family’s needs ahead of everything else. She takes good care of her husband, John and their daughter, Kati. She works hard as a teacher, putting in many hours of work at home as well as giving classes outside the home. When she loses her teaching job at the bank, she takes up Zsolt’s offer to help out at the cafe. Her daughter Kati is always with her. In the beginning, she tries to be supportive and understanding regarding John’s preoccupation with his doppelganger but she soon grows tired and annoyed with John. She sees this as a waste of time, time that can be better spent with his family. Still, no matter how angry she is with her husband, she remains a loyal partner and carries on with her duties as a good wife and mother. When the doppelganger appears to her at the entrance of the cafe, she is not afraid. She also does not ignore his warning, remembering everything that John has shared with her about Janes Szabo. This saves her and Kati from the explosion at the cafe. Q: Based on the novel above, describe the most interesting event you found in the story. Answer with evidence. Ans: The event that I find the most exciting in the novel How I Met Myself is at the very end of the novel, when the explosion at the cafe takes place. John rushes over to the cafe, thinking that Andrea and Kati are there, but upon reaching Felka utca, he hears an explosion. John frantically tries to dig them out of the rubble, with the help of the passers-by. But when the police and firemen arrive, they stop him as it is too dangerous for him to do so. He is told to go home and wait for news about his wife and child. As he is walking home, feeling devastated as he is so sure that he has lost his wife and child, he sees his doppelganger. Janos points to the end of the street. John looks up and sees Andrea and Kati. He is overjoyed. Janos, the doppelganger, has saved their lives. Q: Based on the novel above, write a lesson you have learnt from the novel. Answer with evidence. Ans: The lesson I have learnt from How I Met Myself is that one must be persistent in seeking the truth about something that we wish to understand. John remains persistent in trying to find out more about his doppelganger throughout the novel. He cries his best to make his wife understand the importance of his quest. He doesn’t give up easily even though he faces many challenges. Andrea becomes angry and annoyed with him as a result of all the time he spends researching about his doppelganger. This puts his marriage in trouble. But John is determined to carry on as he knows that it is important for him to understand the reason behind meeting his doppelganger, not just for him, but for his wife and child too. His persistence pays off in the end when he learns about Janos Szabo’s sad story. Q: Based on the novel above, write a character that you dislike the most. Answer with evidence. Ans: The character I dislike in the novel How I Met Myself is Andrea Taylor. Although for the most part she is a loyal and loving wife, there are times when she does not support or try to understand her husband’s predicament. Her husband, John Taylor, is convinced that his doppelganger has an important message to convey to him, most likely involving his wife and child. Therefore, he is determined to find the identity of his doppelganger. Unfortunately, Andrea fails to understand this and gets annoyed with him. She refuses to listen to any more stories about the doppelganger which in the end forces John to investigate the matter in secret. This causes a rift in their marriage. It is ironic that it is the doppelganger who saves her and her child’s life at the end of the story. Q: Based on the novel above, write why you find the novel interesting. Answer with evidence. Ans: I find this novel interesting as it explores the subject of doppelgangers. One snowy night, while walking home from work, John Taylor is knocked over by a stranger in the streets. The man turns around to apologise and to John’s surprise the man looks exactly like him. From this point on, the story gets even more interesting. John tries to find out more about his double. He soon stumbles upon an article on doppelgangers and is then convinced that the man he saw in the streets that fateful night is indeed his doppelganger. It is said that a doppelganger usually appears to give advice or present a warning to the person it appears to. In the end, it is revealed that John’s doppelganger did indeed appear to warn him of the impending danger that involve his wife, Andrea, and his daughter, Kati. Andrea and Kari are saved from the explosion at the cafe thanks to the doppelganger. Q: Based on the novel above, write about a theme in the story. Answer with evidence. Ans: One of the themes in the novel How I Met Myself is love. John Taylor’s love for his wife and daughter spur him on to find out more about his doppelganger and the massage that the doppelganger is trying to convey to him. John realises that it is something important, not only for him, but for his family. The doppelganger, Janos Szabo, lost his wife and child in a tragic bombing during the war. The doppelganger does not want the same devastating fate to befall John. In the end, John’s wife and child are saved from the explosion at the cafe with the doppelganger’s help. Q: Based on the novel above, write about why you like or dislike the ending. Answer with evidence. Ans: I like the happy ending in the novel How I Met Myself. Andrea and Kari are saved from the explosion at the cafe. The doppelganger, Janes Szabo, saves them by warning them not to go into the cafe, John, who initially thinks that he has lost his wife and child, is overjoyed to discover that they are safe. He would have been deeply devastated if he lost them. Q: Based on the novel above, write about what happened to the protagonist or main character at the end of the story. Answer with evidence. Ans: The main character, John Taylor, meets his doppelganger at the very beginning of the story. He is deeply disturbed by this meeting and he is determined to find out the reason why his doppelganger has appeared to him. He realises at the end of the story that his doppelganger had come to warn him of the impending danger to his wife and child. As a result, his wife and child are saved. Q: Based on the novel above, write about the plot in the story. Answer with evidence. Ans: On a snowy evening, John Taylor is on his way home from the office when a man runs into him and knocks him over. The man turns to apologise and John is shocked to see that the man looks exactly like him. The double rushes off leaving no footprints in the snow. John tries to look for the man but he has somehow mysteriously disappeared. From this point on, John becomes almost obsessed with finding out more about his double and why he has met him. From his findings, John learns that the man he saw was his doppelganger and that meeting his doppelganger was no accident. His doppelganger had a very important message for him, that is to warn him of impending danger. In the end, John learns that the doppelganger has saved the lives of his wife and child and he is extremely grateful. Q: Based on the novel above, write about the positive influence that a character has on another character in the novel. Answer with evidence. Ans: The doppelganger, Janos Szabo, has a positive influence on John Taylor. The doppelganger tries to help John by warning him of impending danger. As a result of his doppelganger’s appearance, John learns the meaning of determination and perseverance in his quest to uncover the identity of his doppelganger. He faces many obstacles before he succeeds in doing so. Finding out more about his doppelganger also helps John realise how important his family is to him. When he mistakenly thinks that his family has died in the explosion, he is truly devastated. This makes him appreciate them all the more when he realises that they are alive after all. Q: Based on the novel above, write about the relationship between two characters in the story. Answer with evidence. Ans: In the beginning of the story, John and Andrea have a very close and loving relationship. But once the doppelganger appears to John and he becomes almost obsessed with finding out whatever he can about the doppelganger, Andrea grows annoyed and angry with John. She feels that he should be spending more time with his family. Their marriage becomes strained. Towards the end of the novel, John and Andrea are barely on speaking terms. But, when the doppelganger appears to Andrea and saves her and Kati from the explosion at the cafe, things between John and Andrea get bette How to cite How I Met Myself, Papers

The Productivity of Information Technology Essay Example

The Productivity of Information Technology Essay THE PRODUCTIVITY OF INFORMATION TECHNOLOGY: Review and Assessment Erik Brynjolfsson CCS TR #125 December, 1991 This research was sponsored by the MIT Center for Coordination Science, the MIT International Financial Services Research Center, and the Sloan Foundation. Special thanks are due Michael Dertouzos and Tom Malone for encouraging me to pursue this topic as part of a study group at the MIT Laboratory for Computer Science. I would like to thank Ernie Berndt, Geoffrey Brooke, and Chris Kemerer for valuable comments and Marshall Van Alstyne and Peter Perales for excellent research assistance. Only I am responsible for any remaining deficiencies The Productivity of Information Technology: Review and Assessment Erik Brynjolfsson Abstract Productivity is the bottom line for any investment. The quandary of information technology (IT) is that, despite astonishing improvements in the underlying capabilities of the computer, its productivity has proven almost impossible to assess. There is an increasing perception that IT has not lived up to its promise, fueled in part by the fact that the existing empirical literature on IT productivity generally has not identified significant productivity improvements. However, a careful review, whether at the level of the economy as a whole, among information workers, or in specific manufacturing and service industries, indicates that the evidence must still be considered inconclusive. It is premature to surmise that computers have been a paradoxically unwise investment. A puzzle remains in the inability of both academics and managers to document unambiguously the performance effects of IT. Four possible explanations are reviewed in turn: mismeasurement, lags, redistribution and mismanagement. We will write a custom essay sample on The Productivity of Information Technology specifically for you for only $16.38 $13.9/page Order now We will write a custom essay sample on The Productivity of Information Technology specifically for you FOR ONLY $16.38 $13.9/page Hire Writer We will write a custom essay sample on The Productivity of Information Technology specifically for you FOR ONLY $16.38 $13.9/page Hire Writer The paper concludes with recommendations for investigating each of these explanations using traditional methodologies, while also proposing alternative, broader metrics of welfare that ultimately may be required to assess, and enhance, the benefits of IT. Keywords: Productivity, Computers, Performance measurement, Economic value, Investment justification. CONTENTS The Productivity Paradox A Clash of Expectations and Statistics . 1 Dimensions of the Paradox .. Economy-wide Productivity and Information Worker Productivity . . 7.. The Productivity of Information Technology Capital in Manufacturing 11 The Productivity of Information Technology Capital in Services . 15 Leading Explanations for the Paradox .. 19 Measurement Errors 20 Lags . 5 Redistribution .. 28 Mismanagement . . 229. 9. Con clusio. n.. 32 Summary . . . 32 Where Do We Go From Here? . 34 Tables and Graphs . .. 40 Bibliography . 4477. Information Technology and Productivity The Productivity Paradox A Clash of Expecta tions and Statistics The relationship between information technology (IT) and productivity is widely discussed but little understood. On one hand, delivered computing-power in the US economy has increased by more than two orders of magnitude in the past two decades (figure 1). On the other hand, roductivity, especially in the service sector, seems to have stagnated (figure 2). Given the enormous promise of IT to usher in the biggest technological revolution men have known (Snow, 1966), disillusionment and even frustration with the technology is increasingly evident in statements like No, computers do not boost productivity, at least not most of the time (Economist, 1990) and headlines like Computer Data Overload Limits Productivity Gains (Zachary, 1991) and Computers Arent Pulling Their Weight (Berndt Morrison, 1991a). The increased interest in the productivity paradox, as it has become known, has engendered a significant amount of research, but, thus far, this has only deepened the mystery. The results are aptly characterized by Robert Solows quip that we see computers everywhere except in the productivity statistics, and Bakos and Kemerers (1991) more recent summation that These studies have fueled a controversial debate, primarily because they have failed to document substantial productivity improvements attributable to information technology investments. Although similar conclusions are repeated by an alarming number of researchers in this area, we must be careful not to overinterpret these findings; a shortfall of evidence is not necessarily evidence of a shortfall. Nonetheless, given the increasing significance of IT in the budgets of most businesses and in the nation as a whole, continued investment cannot be justified by blind faith alone. Draft: 1/29/92 page 1 Information Technology and Pr oductivity This paper seeks to contribute to the research effort by summarizing what we know and dont know, by distinguishing the central issues from diversions, and by clarifying the questions that can be profitably explored in future research. After reviewing and assessing the research to date, it appears that the shortfall of IT productivity is at least as likely due to deficiencies in our measurement and methodological tool kit as to mismanagement by developers and users of IT. One can only conclude, as Attewell and Rule (1984) did in an earlier survey, that we still have much o learn about how to measure the effects of computers on organizations. While particular emphasis is placed on economic approaches to both theory and empirics in this review, it is hoped that the process of addressing the productivity mystery will prove to be a useful springboard for other methodologies as well and for examining the broader issues involved. As a prelude to the literature survey, it is useful to define some of the terms used and to highlight some of the basic trends in the economics of IT. Definitions: * Information technology can be defined in various ways. Among the most common is the category Office, Computing and Accounting Machinery of the US Bureau of Economic Analysis (BEA) which consists primarily of computers. Some researchers use definitions that also include communications equipment, instruments, photocopiers and related equipment, and software and related services. * Labor productivity is calculated as the level of output divided by a given level of labor input. Multifactor productivity (sometimes more ambitiously called total factor productivity) is calculated as the level of output for a given level of several inputs, typically labor, capital and materials. In principle, multifactor productivity is a better guide to the efficiency of a firm or industry because it adjusts for shifts among inputs, such as an increase in capital intensity, but lack of data can make this consideration moot. Draft: 1/29/92 page 2 Information Technology and Productivity * In pr oductivity calculations, output is defined as the number of units produced times their unit value, proxied by their real price. Establishing the real price of a good or service requires the calculation of individual price deflators, often using hedonic methods, that eliminate the effects of inflation without ignoring quality changes. Trends: * The price of computing has dropped by half every 2-3 years1 (figure 3a and figure 3b). If progress in the rest of the economy had matched progress in the computer sector, a Cadillac would cost $4. 98, while ten minutes labor would buy a years worth of groceries. 2 * There have been increasing levels of business investment in information technology equipment. These investments now account for over 10% of new investment in capital equipment by American firms3 (figure 4). * Information processing continues to be the principal task undertaken by Americas work force. Over half the labor force is employed in information-handling activities. (figure 5). * Overall productivity growth has slowed significantly since the early 1970s and measured productivity growth has fallen especially sharply in the service sector, which consumes over 80% of IT (figure 2). * White collar productivity statistics have been essentially stagnant for 20 years. figure 6) 1 In the last 35 years, the quality-adjusted costs of computing have decreased by over 6000-fold relative to equipment prices outside the computer sector [Gordon, 1987]. This relationship has been dubbed Moores Law after John Moore who first documented the trend in microprocessors. It is widely projected to continue at least into the next century. 2 This comparison was inspired by the slightly exaggera ted claim in Forbes, [, 1980 #279], that If the auto industry had done what the computer industry has done, Rolls-Royce would cost $2. 50 and get 2,000,000 miles to the gallon. The $4. 98 Cadillac is based on a price of $30,890 for a 1991 Sedan de Ville divided by 6203, the relative deflator for computers. The grocery comparison is based on a wage of $10 an hour and $10,000 worth of groceries, each in actual 1991 dollars. 3 Some studies estimate that as much as 50% of recent equipment investment is in information technology [Kriebel, 1989 #417]. This higher figure seems to be partly due to a broader definition of IT. A discrepancy also arises when recent investments are expressed in 1982 dollars, when IT was relatively more expensive. This has the effect of boosting ITs real share over time faster than its nominal share grows. Draft: 1/29/92 page 3 Information Technology and Productivity These facts suggest two central questions, which comprise the productivity paradox: 1) Why are companies investing so heavily in information technology if it doesnt add to productivity? ) If information technology is contributing to productivity, why have we been unable to measure it? In seeking to answer these questions, this paper builds on a number of previous literature surveys. Much of the material in section III is adapted from an earlier paper with Bruce Bimber (Brynjolfsson Bimber, 1990) which also included an annotated bibliography of 104 related articles and a summary of six explanations for the productivity paradox from outside the economics literature. An earlier study by Crowston and Treacy (1986), identified 11 articles on the impact of IT on enterprise level performance by searching ten journals from 1975 to 1985. They conclude that there had been surprisingly little success in measuring the impact of IT and attribute this to the lack of clearly defined variables which in turn stems from an inadequacy of suitable reference disciplines and methodologies. One natural reference discipline is economics and an excellent review of recent research combining information systems and economics, by Bakos and Kemerer (1991), includes particularly relevant work in sections on macroeconomic impacts of information technology and information technology and organizational performance. Because statistical work is central to the majority of the approaches to assessing IT productivity, another very useful survey is Gurbaxani and Mendelsons (1989) paper on the use of data from secondary sources in MIS research. In addition to summarizing the work that has already been done, they make a convincing case that using pre-compiled data sets has significant advantages over starting de novo with original data, as has been the more common practice among MIS researchers. Finally, many of the papers that seek to directly Draft: 1/29/92 page 4 Information Technology and Productivity assess IT productivity begin with a literature survey. The reviews by Brooke (1991), Barua, Mukhopadhyay and Kriebel (1991), and Berndt and Morrison (1991b) were particularly useful. Although over 150 articles were considered in this review, it cannot claim to be comprehensive. Rather, it aims to clarify for the reader the principal issues surrounding IT and productivity, reflecting the results of a computerized literature search of 30 of the leading journals in both information systems and economics,4 and more importantly, discussions with many of the leading researchers in this area, who helped identify recent research that has not yet been published. The remainder of the paper is organized as follows. The next section summarizes the empirical research that has attempted to measure the productivity of information technology. Section III classifies the explanations for the paradox into four basic categories and assesses the components of each in turn. Section IV concludes with summaries of the key issues identified and some avenues for further research. Dimensions of the Paradox Productivity is the fundamental measure of a technologys contribution. With this in mind, CEOs and line managers have increasingly begun to question their huge investments in computers and related technologies (Loveman, 1988). While major success 4 The journals searched included American Economic Review, Bell (Rand) Journal of Economics, Brookings Papers on Economics and Accounting, Econometrica, Economic Development Review, Economica, Economics Journal, Economist (Netherlands), Information Economics Policy, International Economics Review, Journal of Business Finance, Communications of the ACM, Database, Datamation, Decision Sciences, Harvard Business Review, IEEE Spectrum, IEEE Transactions on Engineering Management, IEEE Transactions on Software Engineering, Information Management, Interfaces, Journal of Systems Management, Management Science, MIS Quarterly, Operations Research, and Sloan Management Review. Articles were selected if they indicated an emphasis on computers, information systems, information technology, decision support systems, expert systems, or high technology combined with an emphasis on productivity. Draft: 1/29/92 page 5 Information Technology and Productivity stories exist, so do equally impressive failures (see, for example (Kemerer Sosa, 1990; Schneider, 1987)). The lack of good quantitative measures for the output and value created by information technology has made the MIS managers job of justifying investments particularly difficult. Academics have had similar problems assessing the contributions of this critical new technology, and this has been generally interpreted as a negative signal of its value. The disappointment in information technology has been chronicled in articles disclosing broad negative correlations with economy-wide productivity and information worker productivity. Econometric estimates have also indicated low IT capital productivity in a variety of manufacturing and service industries. The principal empirical research studies of IT and productivity are listed in table 1. Draft: 1/29/92 page 6 Information Technology and Productivity Table 1: Principal Empirical Studies of IT and Productivity Economy-wide Cross-sector or (Jonscher, 1983; Jonscher, 1988) (Baily Chakrabarti, 1988; Baily, 1986b; Baily Gordon, 1988) (Roach, 1987a; Roach, 1988; Roach, 1989b) (Brooke, 1991) (Osterman, 1986) (Grove, 1990) (Dos Santos, Peffers Mauer, 1991) Manufacturing (Berndt Morrison, 1991b) (Siegel Griliches, 1991) (Loveman, 1988) (Weill, 1988) (Dudley Lasserre, 1989) (Morrison Berndt, 1990) (Barua, Kriebel Mukhopadhyay, 1991) Services (Cron Sobol, 1983) (Strassman, 1985) (Baily, 1986a) (Roach, 1991; Roach, 1987b; Roach, 1989a) (Noyelle, 1990) (Brand Duke, 1982) (Pulley Braunstein, 1984) (Bender, 1986) (Bresnahan, 1986) (Franke, 1987) (Harris Katz, 1988; Harris Katz, 1989) (Parsons, Gotlieb Denny, 1990) (Weitzendorf Wigand, 1991) Economv-wide Productivity and Information Worker Productivitv The Issue One of the core issues for economists in the past decade has been the productivity slowdown that began in the early 1970s. There has been a drop in labor productivity growth from about 2. 5% per year between 1953-1968 to about 0. 7% per year from 1973- 1979. Multi-factor productivity growth, which takes into account changes in capital, declined from 1. 75% a year to 0. 32% over the same periods (Baily, 1986b). Even after accounting for factors such as the oil price shocks, changes in labor quality and potential measurement errors, most researchers still find that there is an unexplained residual drop in Correlations Models II . w w If i Draft: 1/29/92 page 7 i Draft: 1/29/92 Information Technology and Productivity page 8 productivity as compared with the first half of the post-war period. The sharp drop in productivity roughly coincided with the rapid increase in the use of information technology (figure 1). Although recent productivity growth has rebounded somewhat, especially in manufacturing, the overall negative correlation between economy-wide productivity and the advent of computers is at the core of many of the arguments that information technology has not helped US productivity or even that information technology investments have been counter-productive (Baily, 1986b). This link is made more explicit in research by Stephen Roach (1987a; 1988) focusing specifically on information workers, regardless of industry. While in the past, office work was not very capital intensive, recently the level of information technology capital per (white collar) information worker has begun approaching that of (blue collar) production capital per production worker. Concurrently, the ranks of information workers have ballooned and the ranks of production workers have shrunk. Roach cites statistics indicating that output per production worker grew by 16. 9% between the mid- 1970s and 1986, while output per information worker decreased by 6. 6%. He concludes: We have in essence isolated Americas productivity shortfall and shown it to be concentrated in that portion of the economy that is the largest employer of white-collar workers and the most heavily endowed with high-tech capital. Roachs analysis provides quantitative support for widespread reports of low office productivity. 5 A more sanguine explanation is put forth by Brooke (1991). Although he confirmed a broad-level correlation with declines in productivity, he hypothesized that this was due to increases in product variety which resulted in commensurate reductions in economies of scale. This hypothesis was supported by his finding of a positive correlation 5 For instance, Lester Thurow has noted that the American factory works, the American office doesnt, citing examples from the auto industry indicating that Japanese managers are able to get more output from blue collar workers (even in American plants) with up to 40% fewer managers. III Information Technology and Productivity between IT investment and the number of trademark applications. Because variety generally has positive value to consumers, but is ignored by conventional measures of productivity, this finding suggests a measurement problem, which is explored more fully in below in the section on mismeasurement. Comment Upon closer examination, the alarming correlation between IT and lower productivity at the level of the entire US economy is not compelling because so many other factors affect output and therefore productivity. Until recently, computers were not a major share of the economy. Consider the following order of magnitude estimates. Information technology capital stock is currently equal to about 10% of GNP, or total output. If, hypothetically, IT were being used efficiently and its marginal product were 20% (exceeding the return to most other capital investments), then current GNP would be directly increased about 2% (10% x 20%) because of the existence of our current stock of IT. However, information technology capital stock did not jump to its current level in the past year alone. Instead, the increase must be spread over about 30 years, suggesting an average contribution to aggregate GNP growth of 0. 06% in each year. 6 This would be very difficult to isolate because so many other factors affected GNP, especially in the relatively turbulent 1970s and early 1980s. Indeed, if the marginal product of IT capital were anywhere from -20% to +40%, it would still not have affected aggregate GNP growth by more than about 0. 1% per year and productivity growth by even less. 7 6 In his comment on Baily and Gordon (1988), David Romer notes that a similar argument applies to almost any capital investment. 7 In dollar terms, each white collar worker is endowed with about $10,000 in IT capital, which at a 20% ROI, would increase his or her total output about by about $2000 per year as compared with pre-computer levels of output. Compare to the $100,000 or so in salary and overhead that it costs to employ this worker and the expectations for a technological silver bullet seem rather ambitious. Draft: 1/29/92 page 9 Information Technology and Productivity This is not to say that computers may not have had significant effects in specific areas, like transaction processing, or on other characteristics of the economy, like employment shares, organizational structure or product variety. Rather it suggests that very large changes in capital stock are needed to measurably change total output under conventional assumptions about typical rates of return. However, the growth in information technology stock is still strong and the share of the total economy accounted for by computers is becoming quite substantial. Presumably, if computers are productive, we should begin to notice changes at the level of aggregate GNP in the near future. As for the apparent stagnation in white collar productivity, one should bear in mind that relative productivity cannot be directly inferred from the number of information workers per unit output. For instance, if a new delivery schedule optimizer allows a firm to substitute a clerk for two truckers, the increase in the number of white collar workers is evidence of an increase, not a decrease, in their relative productivity and in the firms productivity as well. Osterman (1986) suggests that this is why clerical employment often increases after the introduction of computers and Berndt and Morrison (199lb) confirm that information technology capital is, on average, a complement for white collar labor even as it leads to fewer blue collar workers. Unfortunately, more direct measures of office worker productivity are exceedingly difficult. Because of the lack of hard evidence, Panko (1984; 1991) has gone so far as to call the idea of stagnant office worker productivity a myth, although he cites no evidence to the contrary. Independent of its implications for productivity, growth in the white collar work force cannot be entirely blamed on information technology. Although over 38% of workers now use computers in their jobs8, the ranks of information workers began to 8 According to the US National Center for Education Statistics, 38. 3% of persons in the 1989 Current Population Survey used computers at work, including nearly 60% of those with four or more years of college. Interestingly, Kreuger [, 1991 #411] finds that workers using computers are paid an average wage premium of 8%, even after controlling for education, computer literacy and other factors. Draft: 1/29/92 page 10 Information Technology and Productivity surge well before the advent of computers (Porat, 1977). Jonscher (1988) even goes so far as to argue that causality goes the other way: the increased demand for information enabled economies of scale and learning in the computer industry, thereby reducing costs. These mitigating factors notwithstanding, the low measured productivity at the level of the whole economy and among white collar workers, especially in the face of huge increases in the accompanying capital stock, does call for closer scrutiny. A more direct case for weakness in information technologys contribution comes from the explicit evaluation of information technology capital productivity, typically by estimating the coefficients of a production function. This has been done in both manufacturing and service industries, and we review each in turn. The Productivity of Information Technology Capital in Manufacturing The Issues There have been at least seven studies of IT productivity in the manufacturing sector, summarized in table 2. A study by Gary Loveman (1988) provided some of the first econometric evidence of a potential problem when he examined data from 60 business units. 9 As is common in the productivity literature, he used ordinary least squares regression and assumed that production functions could be approximated by a Cobb-Douglas function. By taking the logarithm of all variables, he was able to estimate a linear relationship between changes in the log of output 0Â ° (q) and changes in the log of spending on key inputs, including 9 Namely, the Management Productivity of IT (MPIT) subset of the PIMS data set. 10 Where output was defined as (sales + net change in inventories)/ price index. Draft: 1/29/92 page 11 Information Technology and Productivity materials (m), purchased services (ps), labor (1), traditional capital (k), and information technology capital (c), while allowing for an exogenous time trend (), and an error term (? ): q = Blm + B2ps + 1331 + 4k + 135c + X + ? (1) Loveman estimated that the contribution of information technology capital to output (135) was approximately zero over the five year period studied in almost every subsample he examined. His findings were fairly robust to a number of variations on his basic formulation and suggest a paradox: while firms were demonstrating a voracious appetite for a technology experiencing radical improvements, measured productivity gains were insignificant. While Lovemans dependent variable was final output, Barua, Kriebel and Mukhopadhyay (1991) traced Lovemans results back a step by looking at ITs effect on intermediate variables such as capacity utilization, inventory turnover, quality, relative price and new product introduction. Using the same data set, they found that IT was positively related to three of these five intermediate measures of performance, although the magnitude of the effect was generally too small to measurably affect final output. Dudley and Lasserre (1989) also found econometric support for the hypothesis that better communication and information reduce the need for inventories, without explicitly relating this to bottom-line performance measures. Using a different data set, Weill (1988) was also able to disaggregate IT by use, and found that significant productivity could be attributed to transactional types of information technology (e. g. data processing), but was unable to identify gains associated with strategic systems (e. g. sales support) or informational investments (e. g. email infrastructure). Draft: 1/29/92 page 12 Information Technology and Productivity Morrison and Berndt have written two papers using a broader data set from the US Bureau of Economic Analysis (BEA) that encompasses the whole U. S. manufacturing sector. The first (Morrison Berndt, 1990), which examined a series of highly parameterized models of production, found evidence that every dollar spent on IT delivered, on average, only about $0. 80 of value on the margin, indicating a general overinvestment in IT. Their second paper (Berndt Morrison, 1991b) took a less structured approach and examined broad correlations of IT with labor productivity and multifactor productivity, as well as other variables. This approach did not find a significant difference between the productivity of IT capital and other types of capital for a majority of the 20 industry categories examined. They did find that IT was correlated with significantly increased demand for skilled labor. Finally, Siegel and Griliches (1991) used industry and establishment data from a variety of sources to examine several possible biases in conventional productivity estimates. Among their findings was a positive simple correlation between an industrys level of investment in computers and its multifactor productivity growth in the 1980s. They did not examine more structural approaches, in part because of troubling concerns they raised regarding the reliability of the data and government measurement techniques. Draft: 1/29/92 page 13 Draft: 1/29/92 Information Technology and Productivity page 14 Table 2: Studies of IT in Manufacturing Study Data source Findings Loveman, 1988) PIMS/MPIT IT investments added nothing to output (Weill, 1988) Valve manufacturers Contextual variables affect IT performance (Dudley Lasserre, IT and communication reduces inventories 1989) (Morrison Berndt, BEA IT marginal benefit is 80 cents per dollar 1990) invested (Barua, Kriebel PIMS/MPIT IT improved inte rmediate outputs, if not Mukhopadhyay, 1991) necessarily final output (Berndt Morrison, BEA, BLS IT not correlated with higher multi-factor 1991 b) productivity in most industries, more labor use (Siegel Griliches, Multiple govt sources IT using industries tend to be more 1991) productive; government data is unreliable Comment All authors make a point of emphasizing the limitations of their respective data sets. The MPIT data, which both Loveman and Barua, Kriebel and Mukhopadhyay use, can be particularly unreliable. As Loveman is careful to point out, his results are based on dollar denominated outputs and inputs, and therefore depend on price indices which may not accurately account for changes in quality or the competitive structure of the industry. The results of both of these studies may also be unrepresentative to the extent that the relatively short period covered by the MPIT data, 1978- 83, was unusually turbulent. The BEA data may be somewhat more dependable but are subject to subtle biases due to the unintuitive techniques used to aggregate and classify establishments. One of Siegel and Griliches principal conclusions was that after auditing the industry numbers, we found that a non-negligible number of sectors were not consistently defined over time. However, the generally reasonable estimates derived for the other, non-information technology factors of production in each of the studies indicate that there may indeed be something worrisome, or at least special, about information technology. Additional III Information Technology and Productivity econometric work would go far toward establishing whether these results are an artifact of the data or a genuine puzzle in need of more thorough analysis. The Productivity of Information Technology Capital in Services The Issues It has been widely reported that most of the productivity slowdown is concentrated in the service sector (1991; Roach, 1987b; Schneider, 1987). Before about 1970, service productivity growth was comparable to that in manufacturing, but since then the trends have diverged significantly. Meanwhile services have dramatically increased as a share of total employment and to a lesser extent, as a share of total output. Because services use over 80% information technology, this has been taken as indirect evidence of poor information technology productivity. The studies that have tried to assess IT productivity in the service sector are summarized in table 3. One of the first studies of ITs impact was by Cron and Sobol (1983), who looked at a sample of wholesalers. They found that on average, ITs impact was not significant, but that it seemed to be associated with both very high and very low performers. This finding has engendered the hypothesis that IT tends to reinforce existing management 11 According to government statistics, from 1953 to 1968, labor productivity growth in services averaged 2. 56%, vs. 2. 61% in manufacturing. For 1973 to 1979, the figures are 0. 68% vs. 1. 53%, respectively (Baily, 1986). However, a recent study (Gordon, 1989) suggests that measurement errors in US statistics systematically understate service productivity growth relative to manufacturing. More recently, computers definitely have caused some divergence in the statistics on manufacturing and service productivity, but for a very different reason. Because of the enormous quality improvements attributed to the computers, the nonelectrical machinery category (containing the computer producing industry) has shown tremendous growth. As a result, while overall manufacturing productivity growth has rebounded from about 1. 5% in the 1970s to 3. 5% in the 1980s, about two thirds of this increase is simply attributable to the greater production (as opposed to use) of computers (see comment by William Nordhaus on Baily Gordon, 1988 and section III. A of this paper) Draft: 1/29/92 page 15 Information Technology and Productivity approaches, helping well-organized firms succeed but only further confusing anagers who havent properly structured production in the first place. Strassman (1985; 1990) also reports disappointing evidence in several studies. In particular, he found that there was no correlation between IT and return on investment in a sample of 38 service sector firms: some top performers invest heavily in IT, while some do not. In his most recent book (1990), he concludes that there is no relation between spending for computers, profits and productivity. Roachs widely cited research on white collar productivity, discussed above, focused principally on ITs dismal performance in the service sector (1991; 1987a; 1987b; 1988; 1989a; 1989b). Roach argues that IT is an effectively used substitute for labor in most manufacturing industries, but has paradoxically been associated with bloating whitecollar employment in services, especially finance. He attributes this to relatively keener competitive pressures in manufacturing and foresees a period of belt-tightening and restructuring in services as they also become subject to international competition. There have been several studies of ITs impact on the performance of various types of financial services firms. A recent study by Parsons, Gottlieb and Denny (1990) estimated a production function for banking services in Canada and found that overall, the impact of IT on multifactor productivity was quite low between 1974 and 1987. They speculate that IT has positioned the industry for greater growth in the future. Similar conclusions are reached by Franke (1987), who found that IT was associated with a sharp drop in capital productivity and stagnation in labor productivity, but remained optimistic about the future potential of IT, citing the long time lags associated with previous technological transformations such as the conversion to steam power. On the other Draft: 1/29/92 page 16 Information Technology and Productivity hand, Brand (1982), using BLS data and techniques, found that moderate productivity growth had already occurred in banking. Harris and Katz (1988; 1989) and Bender (1986) looked at data on the insurance industry from the Life Office Management Association Information Processing Database. They found a positive relationship between IT expense ratios and various performance ratios although at times the relationship was quite weak. Several case studies of ITs impact on performance have also been done, including one by Weitzendorf Wigand (1991) which developed a model of information use in two service corporations, and a study of an information services firm by Pulley and Braunstein (1984), which found an association with increased economies of scope. Table 3: Studies of IT in Services Study Data source Findings (Brand Duke, 1982) BLS Productivity growth of 1. 3%/yr in banking (Cron Sobol, 1983) 138 medical supply Bimodal distribution among high IT wholesalers investors: either very good or very bad (Pulley Braunstein, Monthly data from Significant economies of scope 1984) information service firm (Clarke, 1985) Case study Major business process redesign needed to reap benefits in investment firm Strassman, 1985; Computerworld survey No correlation between various IT ratios Strassman, 1990)] of 38 companies and performance measures (Bender, 1986) LOMA insurance data on Weak relationship between IT and variou s 132 firms performance ratios (Bresnahan, 1986) Financial services firms Large gains in imputed consumer welfare (Franke, 1987) Finance industry data (Roach, 1991; Roach, Principally BLS, BEA Vast increase in IT capital per information 1987b; Roach, 1989a) worker while measured output decreased (Harris Katz, 1988; LOMA insurance data Weak positive relationship between IT and Harris Katz, 1989) for 40 various performance ratios Noyelle, 1990) US and French industry Severe measurement problems in services (Parsons, Gotlieb Internal operating data IT coefficient in translog production Denny, 1990) from 2 large banks function small and often negative (Weitzendorf Interviews at 2 Interactive model of information use Wigand, 1991) companies Draft: 1/29/92 page 17 Information Technology and Productivity Comment Measurement problems are even more acute in services than in manufacturing. In part, this arises because many service transactions are idiosyncratic, and therefore not subject to statistical aggregation. Unfortunately, even when abundant data exist, classifications sometimes seem arbitrary. For instance, in accordance with a fairly standard approach, Parsons, Gottlieb and Denny (1990) treated time deposits as inputs into the banking production function and demand deposits as outputs. The logic for such decisions is often difficult to fathom and subtle changes in deposit patterns or classification standards can have disproportionate impacts. The importance of variables other than IT also becomes particularly apparent in some of the service sector studies. Cron and Sobols finding of a bimodal distribution suggests that some variable was left out of the equation. Furthermore, researchers and consultants have increasingly emphasized the theme of re-engineering work when introducing major IT investments (Davenport Short, 1990; Hammer, 1990). A frequently cited example is the success of the Batterymarch services firm, as documented by Clarke (1985). Batterymarch used information technology to radically restructure the investment management process, rather than simply overlaying IT on existing processes. In sum, while a number of the dimensions of the information technology productivity paradox have been overstated, the question remains as to whether information technology is having the positive impact expected. In particular, better measures of information worker productivity are needed, as are explanations for why information technology capital hasnt clearly improved firm-level productivity in manufacturing and services. We now examine four basic approaches taken to answer these questions. Draft: 1/29/92 page 18 Information Technology and Productivity Leading Explanations for the Paradox Although it is too early to conclude that ITs productivity contribution has been subpar, a paradox remains in our inability to unequivocally document any contribution after so much effort. The various explanations that have been proposed can be grouped into four categories: 1) Mismeasurement of outputs and inputs, 2) Lags due to learning and adjustment, 3) Redistribution and dissipation of profits, 4) Mismanagement of information and technology. The first two explanations point to shortcomings in research, not practice, as the root of the productivity paradox. It is possible that the benefits of IT investment are quite large, but that a proper index of its true impact has yet to be analyzed. Traditional measures of the relationship between inputs and outputs fail to account for non-traditional sources of value. Second, if significant lags between cost and benefit may exist, then short-term results look poor but ultimately the pay-off will be proportionately larger. This would be the case if extensive learning, by both individuals and organizations, were needed to fully exploit IT, as it is for most radically new technologies. A more pessimistic view is embodied in the other two explanations. They propose that there really are no major benefits, now or in the future, and seek to explain why managers would systematically continue to invest in information technology. The redistribution argument suggests that those investing in the technology benefit privately but at the expense of others, so no net benefits show up at the aggregate level. The final type of explanation examined is that we have systematically mismanaged information Draft: 1/29/92 page 19 Draft: 1/29/92 Information Technology and Productivity page 20 technology: there is something in its nature that leads firms or industries to invest in it when they shouldnt, to misallocate it, or to use it to create slack instead of productivity. Each of these four sets of hypotheses is assessed in turn in this section. Measurement Errors The Issues The easiest explanation for the low measured productivity of information technology is simply that were not properly measuring output. Denison (1989) makes a wide-ranging case that productivity and output statistics can be very unreliable. Most economists would agree with the evidence presented by Gordon and Baily (1989), and Noyelle (1990) that the problems are particularly bad in service industries, which happen to own the majority of information technology capital. It is important to note that measurement errors need not necessarily bias IT productivity if they exist in comparable magnitudes both before and after IT investments. However, the sorts of benefits ascribed by managers to information technology increased quality, variety, customer service, speed and responsiveness are precisely the aspects of output measurement that are poorly accounted for in productivity statistics as well as in most firms accounting numbers. This can lead to systematic underestimates of IT productivity. The measurement problems are particularly acute for IT use in the service sector and among white collar workers. Since the null hypothesis that no improvement occurred wins by default when no measured improvement is found, it probably is not coincidental that service sector and information worker productivity is considered more of a problem than manufacturing and blue collar productivity, where measures are better. III Information Technology and Productivity a. Output Mismeasurement As discussed in the introduction, when comparing two output levels, it is important to deflate the prices so they are in comparable real dollars. Accurate price adjustment should remove not only the effects of inflation but also adjust for any quality changes. Much of the measurement problem arises from the difficulty of developing accurate, quality-adjusted price deflators. Additional problems arise when new products or features are introduced, not only because they have no predecessors for direct comparison, but also because variety itself has value, and that can be nearly impossible to measure. The positive impact of information technology on variety and the negative impact of variety on measured productivity has been econometrically and theoretically supported by Brooke (1991). He argues that lower costs of information processing have enabled companies to handle more products and more variations of existing products. However, the increased scope has been purchased at the cost of reduced economies of scale and has therefore resulted in higher unit costs of output. For example, if a clothing manufacturer chooses to produce more colors and sizes of shirts, which may have value to consumers, existing productivity measures rarely account for such value and will typically show higher productivity in a firm that produces a single color and size. 12 Higher prices in industries with increasing product diversity is likely to be attributed to inflation, despite the real increase in value provided to consumers. In services, the problem of unmeasured improvements can be even worse than in manufacturing. For instance, the convenience afforded by twenty-four hour ATMs is frequently cited as an unmeasured quality improvement (Banker Kauffman, 1988). 12The same phenomenon suggests that much of the initial decline in productivity experienced by centrally-planned economies when they liberalize is spurious. Draft: 1/29/92 page 21 Draft: 1/29/92 Information Technology and Productivity page 22 How much value has this contributed to banking customers? Government statistics implicitly assume it is all captured in the number of transactions, or worse, that output is a constant multiple of labor input! (Mark, 1982) In a case study of the finance, insurance and real estate sector, where computer usage and the numbers of information workers are particularly high, Baily and Gordon (Baily Gordon, 1988) identified a number of practices by the Bureau of Economic Analysis (BEA) which tend to understate productivity growth. Their revisions add 2. 3% per year to productivity between 1973 and 1987 in this sector. 13 b. Information Technology Stock Mismeasurement A related measurement issue is how to measure information technology stock itself. For any given amount of output, if the level of IT stock used is overestimated, then its unit productivity will appear to be less than it really is. Denison (1989) argues that the rapid decreases in the real costs of computer power are largely a function of general advances in knowledge and as a result, the government overstates the decline in the computer price deflator by attributing these advances to the producing industry. If this is true, the real quantity of computers purchased recently is not as great as statistics show, while the real quantity purchased 20 years ago is higher. The net result is that much of the productivity improvement that the government attributes to the computer-producing industry, should be allocated to computer-using industries. Effectively, computer users have been overcharged for their recent computer investments in the government productivity calculations. c. Input Mismeasurement 13 They also add 1. 1% to productivity growth before 1973. III Information Technology and Productivity A third issue is the measurement of other inputs. If the quality of work life is improved by computer usage (less repetitive retyping, tedious tabulation and messy mimeos), then theory suggests that proportionately lower wages can be paid. Thus the slow growth in clerical wages may be an artifact of unmeasured improvements in work life that are not accounted for in government statistics. Baily and Gordon (1988) conjecture that this may also be adding to the underestimation of productivity. To the extent that complementary inputs, such as software, or training, are required to make investments in information technology worthwhile, labor input may also be overestimated. Although spending on software and training yields benefits for several years, it is generally expensed in the same year that computers are purchased, artificially raising the short-term costs associated with computerization. In an era of annually rising investments, the subsequent benefits would be masked by the subsequent expensing of the next, larger, round of complementary inputs. On the other hand, IT purchases may also create long-term liabilities in software and hardware maintenance that are not fully accounted for, leading to an underestimate of ITs impact on costs. d. Methodological Concerns In addition to data problems, the methodology used to assess IT impacts can also significantly affect the results. Alpar and Kim (1990) applied two approaches to the same data set. One approach was based on key ratios and the other used a cost function derived from microeconomic theory. 4 They found that the key ratios approach, which had been 14 An example of the key ratios approach is examining the correlation between the ratio of information processing expenses to total expenses and the ratio of total operating expenses to premium income, as Bender [, 1986 #295] did. An example of the cost function approac h is to use duality theory to derive a cost function from a production function, such as the Cobb-Douglas function described above that was used by Loveman [, 1988 #58]. The exact function used by Alpar and Kim was the translog cost function, which is more general, but which requires the estimation of a large number of parameters. Draft: 1/29/92 page 23 Draft: 1/29/92 Information Technology and Productivity page 24 previously used by Bender (1986) and Cron and Sobol (1983), among others, could be particularly misleading. In an effort to model IT effects more rigorously, several papers have called for the use of approaches derived from microeconomics. Cooper and Mukhopadhyay (1990) advocate a production function approach while frontier methodologies such as data envelopment analysis (DEA) have been proposed by Chismar and Kriebel (1985) and Stabell (1982). A very different approach has been applied in an article by Tim Bresnahan (1986). Recognizing the inherent difficulties in measurement in the financial services sector, Bresnahan made no attempt to directly measure output. Instead, he inferred it from the level of spending on mainframes under the assumption that the unregulated parts of the financial services sector were competitive and were therefore acting as agents for consumers. He found that welfare gains were five times greater than expenditures through 1973. Bresnahans findings serve to underscore the size of the gap between the benefits perceived by the consumers of IT and those measured by researchers using conventional techniques. Comments Output measurement is undoubtedly problematic. Rapid innovation has made information technology-intensive industries particularly susceptible to the problems associated with measuring quality changes and valuing new products. The way productivity statistics are currently kept can lead to bizarre anomalies: to the extent that ATMs lead to fewer checks being written, they can actually lower productivity statistics. Increased variety, improved timeliness of delivery and personalized customer service are additional benefits that are poorly represented in productivity statistics. These are all qualities that are particularly likely to be enhanced by information technology. Because III Information Technology and Productivity information is intangible, increases in the implicit information content of products and services are likely to be under-measured compared to increases in materials content. Nonetheless, some analysts are skeptical that measurement problems can explain much of the slowdown. They point out that by many measures, service quality has gone down, not up. 15 Furthermore, they question the value of variety when it takes the form of six dozen brands of breakfast cereal. Indeed, models from industrial organization theory suggest that while more variety will result from the flexible manufacturing and lower search costs enabled by IT, the new equilibrium can exhibit excess variety making consumers worse off (Tirole, 1988). Denison is in the minority in his view that the government is overestimating the improvements in computing power per dollar. A study by Gordon (1987) found that, if anything, computer prices are declining slightly faster than government statistics show. More recently, a study by Triplett (1989) considered Denisons criticisms but in the end supported the BEA methods. 16 Ultimately, a closer look at productivity statistics reminds researchers that the poor showing of information technology may not rest on an entirely solid foundation simply because the statistics are not as reliable as we would like. Lags The Issues 5 Nordhaus in a comment on Baily and Gordon (1988) recalls the doctors house call, custom tailoring, and windshield wipin g at gas stations, among other relics. 16 Most economists appear to be less concerned than Denison about this bias in the BEA statistics. For instance, a consensus of economists at the June, 1990 NBER conference on productivity concurred with Tripletts conclusions. Draft: 1/29/92 page 25 Information Technology and Productivity A second explanation for the paradox is that the benefits from information technology can take several years to show up on the bottom line. a. Evidence of Lags The idea that new technologies may not have an immediate impact is a common one in business. For instance, a survey of executives suggested that many expected it to take at much as five years for information technology investments to pay-off (Nolan/Norton, 1988). This accords with a recent econometric study by Brynjolfsson et al. (1991a) which found lags of two to four years before the strongest organizational impacts of information technology were felt. Loveman (1988) also found slightly higher, albeit still very low, productivity when small lags were introduced. In general, while the benefits from investment in infrastructure can be large, they are indirect and often not immediate. b. Theoretical Basis for Lags The existence of lags has some basis in theory. Because of its unusual complexity and novelty, firms and individual users of information technology may require some experience before becoming proficient (Curley Pyburn, 1982). According to dynamic models of learning-by-using, the optimal investment strategy sets short term marginal costs greater than short-term marginal benefits. This allows the firm to ride the learning curve and reap benefits analogous to economies of scale (Scherer, 1980). If only short-term costs and benefits are measured, then it might appear that the investment was inefficient. Viewed in this framework, there is nothing irrational about the experimentation phase firms are said to experience in which rigorous cost/benefit analysis is not undertaken (Nolan/Norton, 1988). Because future information technology investments tend to be large Draft: 1/29/92 page 26 Information Technology and Productivity relative to current investments, the learning effect could potentially be quite substantial. A similar pattern of costs and benefits is predicted by an emerging literature that treats investments in information technology as options, with short term costs, but with the potential for long-term benefits (Kambil, Henderson Mohsenzadeh, 1991). Comments One way to address the measurement problem associated with complementary inputs (see section III. A. 1 . c) is to introduce appropriate lags in the estimation procedure. For instance, the purchase of a mainframe computer must generally precede the development of mainframe database software. Software, in turn, usually precedes data acquisition. Good decisions may depend on years of acquired data and may not instantaneously lead to profits. 17 Optimally, a manager must take into account these longterm benefits when purchasing a computer and so must the researcher seeking to verify the benefits of computerization. If managers are rationally accounting for lags, this explanation for low information technology productivity growth is particularly optimistic. In the future, not only should we reap the then-current benefits of the technology, but also enough additional benefits to make up for the extra costs we are currently incurring. However, the credibility of this explanation is somewhat undermined by the fact that American managers have not been noted for their ability to postpone benefits to the future. On the contrary, the risk and uncertainty associated with new technologies can make risk-averse managers require higher, not lower, rates of return before they will invest. Increased familiarity, ease-of-use 17 It has been observation that firms that spend proportionately more money on software appear to be more profitable (Computer Economics Report, 1988) If firms go through a hardware buying phase followed by an applications phase, then this may have more to due with firms being in different stages of a multi-year process than with different technology strategies. Draft: 1/29/92 page 27 Draft: 1/29/92 Information Technology and Productivity page 28 and end-user computing may lead to reduced lags between the costs and benefits of computerization in the future. Redistribution The Issues A third possible explanation is that information technology may be beneficial to individual firms, but unproductive from the standpoint of the industry as a whole or the economy as a whole: IT rearranges the shares of the pie without making it any bigger. a. The Private Value of Information Can Exceed its Social Value There are several arguments for why redistribution may be more of a factor with IT investments than for other investments. For instance, information technology may be used disproportionately for market research and marketing, activities which can be very beneficial to the firm while adding nothing to total output (Baily Chakrabarti, 1988; Lasserre, 1988). Furthermore, economists have recognized for some time that, compared to other goods, information is particularly vulnerable to rent dissipation, in which one firms gain comes entirely at the expense of others, instead of by creating new wealth. As Hirshleifer (1971) pointed out, advance knowledge of demand, supply, weather or other conditions that affect asset prices can be very profitable privately even without increasing total output. This will lead to excessive incentives for information gathering. In a similar spirit, races to be the first to apply an innovation can also lead to rent dissipation (Fudenberg Tirole, 1985). The rapid-fire pace of innovation in the information technology industry might also encourage this form of wasteful investment. III Information Technology and Productivity b. Models of Redistribution Baily and Chakrabarti (1988) run a simulation under the assumption that a major share of the private benefits of information technology result from redistribution. The results are broadly consistent with the stylized facts of increased amounts of information technology and workers without increases in total productivity. 2. Comments Unlike the other possible explanations, the redistribution hypothesis would not explain any shortfall in IT productivity at the firm-level: firms with inadequate IT budgets would lose market share and profits to high IT spenders. In this way, an analogy could be made to models of the costs and benefits of advertising. It is interesting to note that most of the reasons for investing in information technology given by the articles in the business press involve taking profits from competitors rather than lowering costs. 18 Mismanagement The Issues A fourth possibility is that, on the whole, information technology really is not productive at the firm level. The investments are made nevertheless because the decision- 18 Porter and Millar, 1985, is not atypical. They emphasize competitive advantage gained by changes in industry structure, product and service differentiation and spawning of new businesses while devoting about 5% of their space to cost savings enabled by IT. Others ignore cost reductions entirely. Draft: 1/29/92 page 29 Draft: 1/29/92 Information Technology and Productivity page 30 makers arent acting in the interests of the firm. Instead, they are a) increasing their slack, b) signalling their prowess or c) simply using outdated criteria for decision-making. a. Increased scope for managerial slack Many of the difficulties that researchers have in quantifying the benefits of information technology would also affect managers (Baily, 1986a; Gremillion Pyburn, 1985). As a result, they may have difficulty in bringing the benefits to the bottom line if output targets, work organization and incentives are not appropriately adjusted (McKersie Walton, 1988). The result is that information technology might increase organizational slack instead of output or profits. This is consistent with arguments by Roach (1989a) that manufacturing has made better use of information technology than has the service sector because manufacturing faces greater global competition, and thus tolerates less slack. b. Information consumption as a signal Feldman and March (1981) also point out that good decisions are generally correlated with significant consumption of information. If the amount of information requested is more easily observable than the quality of decisions, a signalling model will show that too much information will be consumed. c. Use of outdated management heuristics A related argument derives from evolutionary models (Nelson, 1981). The difficulties in measuring the benefits of information and information technology discussed above may also lead to the use of heuristics, rather than strict cost/benefit accounting to set III Information Technology and Productivity levels of information technology investments. 9 Our current institutions, heuristics and management principles evolved largely in a world with little information technology. The radical changes enabled by information technology may make these institutions outdated (see e. g. (Clarke, 1985; Franke, 1987)). For instance, a valuable heuristic in 1960 might have been get all readily available information before making a decision. The same heuristic today could lead to information overload and chaos (Thurow, 1987). Indeed, Ayres (1989) argues that the rapid speed-up enabled by information technology creates unanticipated bottlenecks at each human in the information processing chain. More money spent on information technology wont help until these bottlenecks are addressed. Indeed, researchers have found that a successful IT implementation process must not simply overlay new technology on old processes (Davenport Short, 1990). At a broader level, several researchers suggest that our currently low productivity levels are symptomatic of an economy in transition, in this case to the information era (David, 1989; Franke, 1987; Gay Roach, 1986). For instance, David makes an analogy to the electrification of factories at the turn of the century. Major productivity gains did not occur for twenty years, when new factories were designed and built to take advantage of electricitys flexibility which enabled machines to be located based on work-flow efficiency, instead of proximity to waterwheels, steam-engines and power-transmitting shafts and rods. Comments While the idea of firms consistently making inefficient investments in IT is anathema to the neoclassical view of the firm as a profit-maximizer, it can be explained 19 Indeed, a recent review of the techniques used by major companies to justify information technology investments [Yamamoto, 1991] revealed surprisingly little formal analysis. See Clemons [, 1991 #284] for an assessment of the IT justification process. Draft: 1/29/92 page 31 Draft: 1/29/92 Information Technology and Productivity page 32 formally by models such as agency theory, employment signalling models and evolutionary economics, which treat the firm as a more complex entity. The fact that firms continue to invest large sums in the technology suggests that the individuals within the firm that make investment decisions are getting some benefit or at least believe they are getting some benefit from IT. For instance, a model of how IT enables managerial slack can be developed using agency theory. The standard result in this literature is that when managers (agent) incentives are not aligned with shareholder (principal) interests, suboptimal investment decisions and effort can result. One little noted feature of most agency models is that the incentives for agents to acquire additional information generally exceed the social benefits. This is because agents can use the information to earn rents and to short-circuit the incentive scheme (Brynjolfsson, 1990a). Thus, information technology investments may be very attractive to managers even when they do little to boost productivity. To the extent that competition reduces the scope for managerial slack, the problem is alleviated. In general, however, we do not yet have comprehensive models of the internal organization of the firm and researchers, at least in economics, are mostly silent on the sorts of inefficiency discussed in this section. Conclusion Summary Research on information technology