Understanding Of Different Learning Theories - 1092 Words

SRINIDHI CHENEGARAPU RAJESHWAR UNDERSTANDING OF DIFFERENT LEARNING THEORIES AND THEIR IMPLICATION AND APPLICATION TO e-LEARNING AND ONLINE LEARNING ABSTRACT: The aim of this paper is to explain the understanding of different learning theories and their implication and application to e-learning and online learning. These theories are classical conditioning, behaviorist theory, information processing theory or cognitive theory and constructivist theory. The paper focuses mainly on how learners should learn from different learning theories and how technology can be used to leveraged to enhance learning theory and move towards knowledge acquisition in one of the learning theory. General words: Theory Keywords: learning, e-learning, behaviorist theory, classical conditioning, cognitive theory and constructivist theory. 1. INTRODUCTION TO LEARNING THEORIES Learning is defined as a behavior as a consequence of exposure to stimuli. There are four different learning theories namely classical conditioning , behaviorist, informative or cognitive processing and constructivist theory. 1.1 CLASSICAL CONDITIONING THEORY In Classical conditioning theory, Pavlov dog is taken as an example where a scientist named Ivan Pavlov experimented on a dog about its response to a stimuli. Initially Pavlov observed that whenever he want to give food to his dog he hit the tuning fork first then provided food to eat and at that moment it started salivating and gradually heShow MoreRelatedThe Learning Theory Influences Everyone s Culture, Ethnicity, Gender, And Social Status1605 Words   |  7 Pages The Learning Theory influences everyone’s culture, ethnicity, gender, and social status, by being from different geographical location and religious background everyone has a unique characteristic, when it comes to learning or problem solving. One of the most important events in a human’s life is the â€Å"Learning Theory†. 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Equipment For Operation Iraqi Freedom And Operation...

STATEMENT OF THE PROBLEM What were the causes for the excess and the abandonment of equipment for Operation Iraqi Freedom and Operation Enduring Freedom? BACKGROUND Most logistical tacticians have a tendency to review historical documents before developing strategies to deploy and redeploy troops and equipment. This common practice is very successful to deploying soldiers and equipment, but historically there is a lack of emphasis on the redeployment, or retrograde of equipment. The soldiers are undoubtedly brought home; nonetheless antiquity shows us equipment is sometimes not a priority to return. Logistic American retrograde issues were first publically noticed in 1847 following war with Mexico. A published Army bulletin revealed property divesting as an issue and needed a high priority because of the great loss of left behind equipment. Again after World Wars I and II, the military had immense amounts of equipment scattered across the Pacific and Europe. There was no specific need for the equipment after the war, and much of it was abandoned in place, and although lack of retrograde operations occurred, the abandoned equipment turned useful in supporting the Korean War. Logisticians learning their lessons from previous wars, vowed to not be unprepared while entering the Vietnam War. Specialized programs and systems were established to document, classify and store all equipment entering Vietnam. Continental Army Command initialized the program STOP/SEE toShow MoreRelatedThe Lineage Of The 18th Engineer Brigade Essay863 Words   |  4 PagesEngineer Regiment participated in several Central Europe campaigns during World War II. After the Regiment’s reorganization, the 18th Engineer Brigade participated in multiple campaigns in Vietnam, Operation Desert Storm, Operation Desert Shield, Operation Iraqi Freedom, and Operation Enduring Freedom. 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The 1776th was also given credit for their participation in the Rhineland campaign during their time in France. After a brief stay in France the 1776th engineer company was on the move to Germany. They arrivedRead MoreA Comparison Of The United States And Qatar Relations1091 Words   |  5 Pagesâ€Å"The Pentagon on Tuesday renewed praise of Qatar for hosting a vital U.S. air base and for its enduring commitment to regional secu rity, sticking to a message of reassurance even as President Donald Trump, via Twitter, applauded a decision by Arab powers to cut ties to the Gulf ally.† Pike, J., Mr. (Ed.). (2017, June 06). The United States and Qatar Relations have been on an up rise for the last couple years. Being that Qatar is listed as one of the wealthiest countries in the world remaining

Cyber Laws free essay sample

Out of 20 Internal Assignment marks per paper, 5 marks will be awarded for regularity (attendance) to Counseling/ Contact Programme classes pertaining to the paper. Therefore, the topics given below are only for 15 marks each paper. PART-I Paper-I: Introduction to legal theory and law social transformation Answer ANY TWO of the following questions (2 x 7 ? = 15 Marks) 1. Explain the following theories of law. 1. Law as the Dictate of Reason. 2. Law as the System of Rules 2. Explain the various sources of Law. 3. Write Short notes on the following: 1. Law and Social change 2. Alternative dispute resolution Paper-II: National Legal System Answer ANY TWO of the following questions (2 x 7 ? = 15 Marks) 1. Explain the Fundamental Rights given to the citizens under the Indian Constitutions. 2. Discuss the general principles of legal contract. 3. Write Shorts notes on. 1. Tortious liability and Defense. 2. Negotiable Instruments. PART-II Paper-III: Cyber Law-I Answer the following questions (2 x 7 ? = 15 Marks) 1. Describe the principles of Data Protection. 2. Explain the Transborder data flows and National Control over data flows. We will write a custom essay sample on Cyber Laws or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page 3. Write a note on U. K. Data Protection Act. Contd†¦ Paper-IV: Cyber Law-II Answer ANY TWO of the following questions (2 x 7 ? = 15 Marks) 1. Explain the History and development of Internet. 2. What is Domain name? Discuss the problems of Domain names. 3. Write a note on protection of Computer Software and Liability of Internet Service providers. Paper-V: Cyber Law-III Answer ANY TWO of the following questions (2 x 7 ? = 15 Marks) 1. Write a note on the evolution of concept of Cyber Crime. 2. Discuss various types of Cyber Crime. 3. Write a note on salient features of Information Technology Act 2000. o

Mozart Essays (1903 words) - Music, Classical Music, Mozart Family

Mozart "The classical period produced more instrumental than vocal music, a wealth of serious and comic operas as well as vocal religious music also appeared during this time"(Ferris, 231). One of the best composer of this time was Wolfgang Amadeus Mozart. In this paper I will go through his childhood, his friends and family, and of course his music. Enjoy!!! Child of the Enlightenment The world that Wolfgang Amadeus Mozart entered ceremoniously in 1756 was brimming in change. Historians refer to this era as the Age of Enlightenment, one of unparalleled scientific, philosophical, and political ferment. Within Mozart's lifetime it set in motion forces that would fundamentally alter life not only in his native, Salzburg, but also around the globe. The Enlightenment was not, to be sure, a democratic movement. In France, the absolutism of the Sun King, Louis XIV, continued under Louis XV and XVI. But in Austria, Empress Maria Theresa introduced a greater measure of tolerance and freedom among her subjects, laying a foundation for the democratic revolutions that followed. Wolfgang's father Leopold came from a family of Augsburg bookbinders. He received a solid Jesuit education, more intellectual than evangelical after a year at the Benedictine University in nearby Salzburg; Leopold stopped attending classes to pursue a career as a musician. "Leopold figured as Mozart's most important first model. He taught his son the clavier and composition"(Mercardo 763). Wolfgang's mother Anna-Maria brought as much talent to her 32-year marriage as did Leopold. Though deprived of a formal education, she was highly intelligent and quick-witted? qualities that attracted the sober and reserved Leopold. Only two of their seven children survived infancy. Wolfgang's musically talented sister Nannerl was five years older. Yet in this painting, the 12-year- old looks like a spinster of seventy?complete with budding double chin. Wolfgang, too, looks far older than his 7 years, and controls the action from his place at its center. The Child Prodigy Indeed, Mozart marks the beginning of the Western fascination with the child prodigy. Dressed in the festive outfit given Wolfgang in 1762 by the Empress Maria Theresa, this boy of not quite seven years old looks, for all the world, like a miniature adult who has simply skipped childhood. "Mozart was keenly aware of his exceptional ability, which had been fostered and rutted in him by his father from a very early age"(Schroter). Other nineteenth-century artists represented Wolfgang?variously said to be anywhere from 11 to 14 as a curly-locked angel. For them, how else could the divine music that poured out of a child-size body be explained? The idealization of Mozart's genius was complete by the end of the nineteenth century. Mozart composes with his violin in one hand and music has appeared miraculously on his stand in the other. The message is unmistakable: "Mortals use quills, Mozart simply wills"(Solomon) On the Road The temptation to take his two prodigies on the road proved irresistible to Leopold, who assumed sole responsibility for Mozart's education. Between 1762 and 1766, the Mozarts appeared at almost every major court in Europe. Wolfgang dazzled audiences with his ability to read difficult music at sight and to improvise. In London, as elsewhere, the Mozarts hobnobbed with the leading musicians. Probably the most important of these was Johann Christian Bach, the youngest son of Johann Sebastian. It is no accident that Mozart's early symphonies, composed in London, are often stylistically indistinguishable from those of J. C. Bach. When Mozart was 13, his prowess as a keyboard player, violinist, improviser, and composer were already legendary. "When Mozart was 21 he wrote "Paris" Symphony, N31 while he was in Paris looking for a music position. He was thoroughly disenchanted with the French and their music"(Internet). From 1768 to 1775, between stays in Salzburg, he and Leopold made three further forays to Italy and Germany. Wolfgang evolved from a prodigy into a serious composer. Public Successes A self-confident Mozart assured his father in 1782 that he would be able to support a wife and family in Vienna, As a result which he called "Clavierland. Of its earlier devastation, the dominant architectural style in Vienna is Baroque, aided in the 1700s by an influx of Italian sculptors, stucco workers, and painters. The dominant architect and architectural historian was Italian-trained Johann Fischer von Erlach(1656-1723), whose densely decorated structures still stand out today." He planned to achieve this by writing music for the public: operas, symphonies, and concertos featuring himself as pianist. Although public performances were less frequent than today, they were for that reason on a more lavish scale. Of a set of piano concertos, Mozart

Hathorne and Danforth Essay Example

Hathorne and Danforth Essay Example Hathorne and Danforth Paper Hathorne and Danforth Paper who is shortly followed by Susanna Walcotts allege of freezing too. And later on in the scene when Abigail claims to see Mary Warrens spirit in the form of a bird in the ceiling, instantly Mercy Lewis shouts Its on the beam! Susanna Walcott follows again by saying Her claws, shes stretching her claws! Miller uses Abigails power of leadership she has over her peers to not only show hr power to lead and bully, but also to illustrate the effect of hysteria in such a small community. This is shown again to the audience, when in Act One, Miller presents Abigail to start reeling off the accusations of witchery in Salem. I want to open myself Abigail claims to Hale. Betty later follows with the accusations: I saw George Jacobs with the Devil! I saw Goody Howe with the Devil! these accusations continue until Miller lets the curtain fall at the end of the act.

What Is the Definition of an Earmark in Politics

What Is the Definition of an Earmark in Politics The term earmark spending refers to a part of a spending bill that allocates money for a specific thing such as a location, project or institution. The key difference between an earmark and a general budget line is the specificity of the recipient, which is usually a particular project in a specific Congressmans district or a Senators home state. Earmarking is often used as a tool for negotiation and deal-making: a representative might vote in favor of a project in another representatives district in exchange for earmarked funding in his own district. Definition of Earmark Funding Earmarks are funds provided by the Congress for specific projects or programs in such a manner that the allocation (a) circumvents a merit-based or competitive allocation process; (b) applies to a very limited number of individuals or entities; or (c) otherwise curtails the ability of the Executive Branch to independently manage the agency budget. Thus, an earmark circumvents the appropriations process, as outlined in the Constitution, where Congress grants a lump sum of money to a Federal agency each year and leaves the management of that money to the Executive Branch. Congress includes earmarks in both appropriation and authorization bills orOR in report language (the committee reports that accompanies reported bills and the joint explanatory statement that accompanies a conference report). Because earmarks can be tucked away in report language, the process is not easily identified by constituents. Examples of Earmark Spending Earmark spending relates only to funds identified for specific projects. For instance, if Congress passed a budget that gave a certain sum to the National Park Service as an entity, that wouldnt be considered an earmark. But if Congress added a line indicating that some of the money had to be allocated to preserve a specific landmark, then thats an earmark. Earmark spending may be allocated for (among other things): Research projectsDemonstration projectsParksLaboratoriesAcademic grantsBusiness contracts Some earmarks stand out easily, like a $500,000 grant to the Teapot Museum. But just because an item of expenditure is specific, that doesnt make it an earmark. In defense spending, for instance, bills come with a detailed account of how each dollar will be spent- for example, the amount of money needed to purchase a specific fighter plane. In another context, this would merit an earmark, but not for the Defense Department as this is how they do business.   Is "Earmarking" Considered to Be Unethical? Earmarks have a derogatory connotation on Capitol Hill, largely because of specific earkmark spending projects that have little benefit to anyone but the businesses involved in doing the work. One famous example of such of a project is Alaskas infamous â€Å"Bridge to Nowhere.† a $398 million project intended to replace a ferry to an island that is home to just 50 people. Congress imposed a moratorium on earmarks that went into effect in 2011, which banned members from using legislation to direct money to specific projects or organizations in their districts. In 2012, the Senate defeated a proposal to outlaw earmarks but extended the moratorium by a year. Lawmakers try to avoid using the term while still attempting to insert specific spending provisions into bills. Earmarks are also called a variety of different terms including: Member-directed spendingPlus upsBudget enhancementsAdditionsProgrammatic adjustments Lawmakers have also been known to directly call agency officials and ask them to allocate money toward specific projects, without any pending legislation. The is known as â€Å"phone-marking.†

Sharing Your World Coursework Example | Topics and Well Written Essays - 250 words

Sharing Your World - Coursework Example On the other hand, discrimination is an act that denies participation to groups or categories of people due to prejudice. It also includes the act of treating a member of a given group based on the fact that they’re from a given category of people in the society. My elder brother wanted to become a pastor when he was in college. My parents have used the same preconceived idea to judge me, thinking that I might also come up with the same thought of becoming a pastor when I reach college. I’ve felt so bad that my parents can use what happened to my brother to judge me. The prejudices in myself are such like, the fact that my elder brother passed so well in college and became the top in their class, I feel that I would also follow its footsteps and be the best in my class. I need to overcome this prejudice by believing in my own work and discovering that my brother and are two different

Please High Quality Writing in Anthropology Essay

Please High Quality Writing in Anthropology - Essay Example The archeologists named the creature â€Å"homo floresiensis†. It was dated to be about 18,000 years old (Townsley et al 2010). The hobbit, was the size of a three year old child. However, the remains were of a fully grown female of the species. The archeologists also discovered stone tools and butchered remains of pygmy elephants. This implied that the hobbits, in their existence, used fire and were hunters. The magnitude of their activities is however inconsistent with the size of their brains. The creatures brain was smaller than that of a chimpanzee and it therefore becomes difficult to comprehend how such small creatures, with such a small brain, were able to do such sophisticated activities. Upon further investigation, scientists discovered that the anatomy of the creature was similar and resembled that of our early ancestors in Africa which were in existence over three million years ago. The intrigue of this is the fact that this creature lived more recently as compared to the ancestors in Africa. In addition, anthropologist Matt Tocheri found that the wrist bones of the creature had a resemblance to those of the African apes (Nasht et al 2009). Another anthropologist, Bill Jungers, discovered that the bones of the creature were fitting together with those of â€Å"Lucy†, the most celebrated African fossil. The discovery of the â€Å"homo floresiensis† shows the probability of a new human species in existence. In season 37, the NOVA series aired a three part episode entitled â€Å"Becoming Human†. This 3-part series was linked to the â€Å"Alien from Earth† episode because of the resemblance of the â€Å"homo floresiensis† to â€Å"Lucy†, as will be discussed. The

Luxury Brands Essay Example for Free

Luxury Brands Essay Luxury Brands: What Are They Doing About Social Responsibility? David S. Waller, Marketing Discipline Group, University of Technology Sydney Anurag G. Hingorani, Marketing Discipline Group, University of Technology Sydney Abstract Although luxury goods may be synonymous with extravagance, lavishness, and even waste, it may appear to be a contradiction that a number of companies that manufacture and sell luxury brands have also discovered the value of being socially responsible. With growing criticism of the high costs and exploitation in the manufacture of luxury goods, some companies are increasing the extent to which corporate social responsibility and sustainability issues feature in their business practices. This paper will look at the issues regarding luxury brands and social responsibility, and will focus on LVMH Moà «t Hennessy Louis Vuitton, the world‟s largest luxury goods conglomerate. Introduction Despite the recent global financial crisis and continuing economic troubles worldwide, sales of luxury brands are growing. According to the Luxury Goods Worldwide Market Study, luxury spending in 2011 rose 8% to â‚ ¬185 billion ($US274 billion) in 2011, with growth in the US, Europe and China, which was after a fall in sales in 2008 and 2009 (Holmes 2011). Brand names like Chanel, Yves St Laurent, Louis Vuitton and Tiffany Co. have become household names and brands that some people aspire to purchase and wear. However, luxury brands have also been often criticised for being extravagant, overpriced, exploiting third world suppliers, and wasteful when many people are struggling financially. As luxury brands promote themselves to the global audience, some companies are increasing the extent to which corporate social responsibility (CSR) and sustainability issues feature in their business practices. This paper will explore the issues related to luxury brands and social responsibility, with a particular focus on LVMH Moà «t Hennessy Louis Vuitton, the world‟s largest luxury goods conglomerate which includes internationally recognised brands such as Christian Dior, TAG Heuer, Fendi, Marc Jacobs, Guerlain, Kenzo and Givenchy. A content analysis of the 2010 Annual report will reveal the CSR initiatives/activities undertaken by LVMH and some implications for CSR disclosure will be discussed. Background Since some embarrassing corporate ethical and financial disasters, many organisations are taking steps to improve their corporate governance, ethical practice and CSR activities (Agrawal and Chadha, 2005; Margolis and Walsh, 2001). There has been particular interest in CSR, in which there is a â€Å"concern for the impact of all of the corporations activities on the total welfare of society† (Bowman and Haire, 1976, p. 13). CSR activities and disclosure have increased with organisations identifying different types of CSR initiatives that they undertake, including those that relate to work output, HR activities, social/community commitment, and environmental initiatives (Gray, Owen and Maunders, 1987; Luo and Bhattacharya, 2006; Waller 2009; Waller and Lanis, 2009). These CSR activities can help promote a specific image that management would like to portray to its various stakeholders, and counter criticism for other issues that may affect the company. The luxury industry thrives on the creation of an image and the communication of brandassociations. This contributes to the interest in luxury brands by many consumers who might want to portray a particular image or feel a certain way by acquiring and consuming luxury goods and services. Not only consumers but also academic and industry researchers are  interested in luxury brands (Bendell and Kleanthous 2007; Fionda and Moore 2009; Kapferer and Bastien 2009; Phau and Prendergast 2000). Most consumers prefer to purchase a wellknown, reputable brand over a cheaper, unknown brand, especially when making highinvolvement purchases, or products that reflect a buyer‟s personality. Luxury provides selfexpression which reflects class, status, and quality. However, at a time when there is increasing unemployment, economic troubles around the world, and a downturn in sales, there is a concern that a luxury brand is elitist and uncaring for the wider community. In 2007, the WWF-UK measured 10 luxury brands on their environmental, social and governance (ESG) performance – and the brands did not fair well (Bendell and Kleanthous 2007). In relation to the marketing of luxury brands in a world of rich and poor, the report states: â€Å"Luxury brands are experiencing rapid expansion in societies that contain both very rich and very poor people. Such societies can view displays of conspicuous consumption as a threat to social cohesion. This is true, for example, in China, where the authorities in Beijing have banned the use of billboards to advertise luxury products and services. In this context, the credibility of luxury products and services will be derived from their ability to generate wellbeing, not only for consumers, but also for those involved in (or affected by) their production, use, reuse and disposal.† The report ranked the top 10 largest luxury goods companies on an environmental, social and governance (ESG) performance ranking. This was based on: (1) what the companies report to the community; and (2) what media and non-governmental organisations have said about the companies. The companies were given a score out of 100, and graded from A (the best) to F (the worst). Out of the 10 companies, none were graded more than a C+ with LOreal topping the ranking, followed by Hermà ¨s and Louis Vuitton. By being more proactive in their civic responsibilities and keeping within government regulations in their business operations, an organisation can build a reputation as a good corporate citizen. Some CSR activities that luxury brands can undertake include eco-friendly ingredient sourcing, fair pricing, eco-manufacture, and efficient non-wasteful distribution, as well as corporate sponsorship. This study will examine the CSR activities run by LVMH Moà «t Hennessy Louis Vuitton, the world‟s largest luxury goods conglomerate, via a content analysis of the LVMH 2010 Annual Report. The main company information about LVMH is found in Table 1. Table 1: LVMH Moà «t Hennessy Louis Vuitton Company Information Luxury goods, retail Industry Founded Headquarters Products Brands 1987 Paris, France Clothing, cosmetics, fashion accessories, jewellery, perfumes, spirits, watches and wines Includes: Moà «t et Chandon, Hennessy, Glenmorangie, Fendi, Donna Karan, Givenchy, Kenzo, Louis Vuitton, Marc Jacobs, Parfums Christian Dior, Guerlain, Bulgari, TAG Heuer, Zenith, Hublot, DFS, Le Bon Marchà © â‚ ¬20.32 billion â‚ ¬3.032 billion 83,540 Methodology Organisations can communicate their CSR information through a variety of sources such as advertising, annual reports, public relations and their websites. In this study, the annual report was analysed as this is the only document produced regularly to comply with regulatory requirements and is central to the organisation‟s own image (Gray, Kouhy and Lavers 1995). After finding the LVMH 2010 annual report online from the company website (www.lvmh.com), a search was made for a social responsibility section in the report.

DIWALI -THE FESTIVAL OF LIGHTS Essays -- essays research papers

Diwali rituals Diwali, the festival of lights, is one of the important and widely spread holidays celebrated in India. It is a celebration of lights, and for many, it is truly a sensory experience; some families decorate their houses with all sorts of lights and open up to the neighbors, sharing their love and their food. Those celebrating Diwali spend time with family and friends. They perform religious ceremonies to bring in wealth and prosperity for a new year, cook and eat delicious food, design rangolis, light up their lives by lighting diyas (small earthen lamps), candles and sometimes, by lighting fireworks. Diwali is celebrated in honor of the lord Rama, who on this day returned from a forest exile. Diwali is actually the middle day in a five-day festival that rings in the Hindu New Year. For Diwali, I go to festivals and hold pooja at my house The five days of Diwali Diwali is the most important festival celebrated in India. Diwali or Deepawali means an array of lights. It is a festival of lights symbolizing victory of good over evil and the glory of light. Diwali is celebrated as the day that Lord Rama returned to Ayoda after defeating Ravana. Diwali also signifies Harvest Festival. Another legend is Naraksura, a monster who was a troublemaker to the gods. Lord Krishna and Satyabama killed the demon. Diwali is celebrated in five days. The first day of Diwali is called Dhanteras. The second day is called Narak Chatardasi. On this day Lord Krishna destroye...

Boon or Bane

Advantages and Disadvantages of Internet Research Surveys: Evidence from the Literature Ronald D. Fricker, Jr. and Matthias Schonlau RAND E-mail and Web surveys have been the subject of much hyperbole about their capabilities as well as some criticism about their limitations. In this report we examine what is and is not known about the use of the Internet for surveying. Specifically, we consider evidence found in the literature regarding response rates, timeliness, data quality and cost.In light of this evidence, we evaluate popular claims that Internet-based surveys can be conducted faster, better, cheaper, and/or easier than surveys conducted via conventional modes. We find that the reality of cost and speed often does not live up to the hype. Nonetheless, it is possible to implement Internet-based surveys in ways that are effective and cost-efficient. We conclude that the Internet will continue to grow in importance for conducting certain types of research surveys.INTRODUCTION Wit h the advent of the World Wide Web (Web or WWW) and electronic mail (email), the Internet has opened up new vistas in surveying. Rather than mailing a paper survey, a respondent can now be given a hyperlink to a Web site containing the survey. Or, in an e-mail survey, a questionnaire is sent to a respondent via e-mail, possibly as an attachment. As either an alternative or an adjunct to conventional survey modes (e. g. , the telephone, mail, and face-to-face interviewing) Internet-based surveys offer unique new capabilities.For example, a Web survey can relatively simply incorporate multi-media graphics and sound into the survey instrument. Similarly, other features that were once restricted to more expensive interviewer-assisted modes, such as automatic branching and real-time randomization of survey questions and/or answers, can be incorporated into self-administered Web (and some e-mail) surveys. However, not unlike when phone and mail surveys were first introduced, concerns exis t about whether these Internet-based surveys are scientifically valid and how they are best conducted.In the late 1980s and early 1990s, prior to the widespread availability of the Web, e-mail was first explored as a survey mode. As with the Web, e-mail offers the possibility of nearly instantaneous transmission of surveys to recipients while avoiding any postal costs. Early e-mail were primarily ASCII text-based, with rudimentary formatting at best, which tended to limit their length and scope. The only significant advantage they offered over paper was a potential decrease in delivery and response Field Methods, Vol. 14 No. 4, 2002 347-367. 1 imes, though some also hypothesized that the novelty of the new medium might enhance response rates (Parker, 1992; Zhang, 2000). The Web started to become widely available in the early to mid-1990s and quickly supplanted e-mail as the Internet survey medium of choice because it was easy to implement, it provided an improved interface with the respondent, and it offered the possibility of multimedia and interactive surveys containing audio and video. For convenience samples, the Web also offered a way around the necessity of having to know respondents’ e-mail addresses.As a result, â€Å"quick polls† and other types of entertainment surveys have become increasingly popular and widespread on the Web. Internet-based surveys are now in vogue—those conducted via the Web in particular—because of three assumptions: (a) Internet-based surveys are much cheaper to conduct; (b) Internet-based surveys are faster; and, (c) when combined with other survey modes, Internet-based surveys yield higher response rates than conventional survey modes by themselves. Yet, does the evidence in the literature confirm these assumptions?Are Internet-based surveys faster, better, cheaper, and/or easier than surveys conducted via conventional modes? What can we conclude about the strengths and current limitations of Intern et-based surveying from the facts in the literature? In this report we synthesize the literature about the use of the Internet (e-mail and the Web) in the survey process. Other accounts of the literature include Schonlau, Fricker and Elliott (2002), Couper (2000), Dillman (2000), and Tuten et al. (2002). In addition, an extensive source of Web survey literature can be found on the Web at www. ebsm. org. LITERATURE SUMMARY FOR INTERNET-BASED SURVEYS In this section we summarize key characteristics of Internet-based surveys—that is, surveys using the Web and e-mail as a response mode—as documented in the literature. We employed a professional librarian to conduct a thorough literature search in the Social Science Database and the Conference Paper Index database. The Social Science Database indexes more than 1,500 of the most important worldwide social sciences journals since 1972.Additional articles relevant to the social sciences are also incorporated from over 2,400 jo urnals in the natural, physical, and biomedical sciences. The Conference Paper Index provides access to records of the more than 100,000 scientific and technical papers (since 1973) presented at over 1,000 major regional, national, and international meetings each year. Field Methods, Vol. 14 No. 4, 2002 347-367. 2 The literature search yielded 57 papers that were substantively interesting and informative.Here we report on a subset of those articles of direct relevance to this discussion. (Appendix B of Schonlau et al. , 2002, lists 52 papers and we have augmented the list here with an additional five that have appeared since Schonlau et al. was published. ) We consider the following key characteristics of surveys: (1) response rate, (2) timeliness, (3) data quality, and (4) cost. We compare what has been published in the literature about Internet-based surveys to a natural conventional survey alternative: mail.While no survey mode is going to be optimal in all of these areas, we cho se mail because both mail and Internet-based surveys are self-administered, mail surveys tend to be the least expensive of the conventional modes, and virtually all of the comparisons made in the literature are to mail surveys. Response Rates A standard way to summarize survey performance is by comparing response rates among various survey modes. By â€Å"survey mode† (sometimes called response mode) we mean the mode by which the survey itself is conducted: Web, e-mail, mail, etc.In this section, we compare response rates for studies classified into one of three categories: (1) Surveys employing probability sampling or conducting a census that used the Web as the only response mode; (2) Surveys in which respondents were allowed to choose one of several response modes, including at least one Internet-based response mode; and, (3) Surveys in which respondents were assigned one of several response modes, including at least one Internet-based response mode. We begin with results for studies that used the Web as the primary or only response mode with either censuses or robability samples (Table 1). The table is ordered by year and it shows that Web-only research surveys have currently only achieved fairly modest response rates, at least as documented in the literature. Field Methods, Vol. 14 No. 4, 2002 347-367. 3 Table 1. Response Rates for Web-only Surveys Using Probability Samples or Censuses Sample Size 1,602 14,150 Response Rate 42%d 8% Population University of Michigan Students College-bound high school and college students Everingham (2001) 1,298 44% RAND employees Jones and Pitt (1999) 200 19% University staff b 9,522 41% Purchasers of Dillman et al. 1998) computer products c 2,466 38% Purchasers of Dillman et al. (1998) computer products a Most respondents were contacted via their parents, which reduced the response rate. A mail response mode was added late in the survey protocol. b A relatively plain Web survey design was used in this experimental arm. c A relatively fancy Web survey design was used in this experimental arm. d Another 5. 6 percent of partially completed surveys were also received. Survey Couper et al. (2001) a Asch (2001)In fact, the results in Table 1 may overstate response rate performance for research surveys of broader populations because Dillman’s results are based on participants who were initially contacted by phone and had agreed to participate in a Web survey and Everingham’s sample was of a closed population of employees at one company. Jones and Pitt (1999) sampled staff at â€Å"10 universities whose staff directories were available on the WWW† and Couper et al. (2001) surveyed 1,602 University of Michigan students.In all of these cases, the potential survey participants were likely to be more homogeneous and more disposed to respond compared to a random sample of the general population. In addition, because university populations often tend to have greater access to the Inter net, and today’s college students can be expected to be more computer- and Internet-savvy. In Table 2 we summarize the studies published in the literature that allowed the respondent to choose to respond either via the Web or through the mail, ordered in terms of the fraction that responded via the Web.Since for many populations the fraction of respondents that can or will answer via the Web may not be sufficiently large, and mail emerges as the most relevant second mode for a dual mode survey, these studies are important. Field Methods, Vol. 14 No. 4, 2002 347-367. 4 Table 2. Studies Allowing Respondents to Choose a Web or Mail Response Mode Total Sample Size a Study % Chose to Respond by †¦ Mail Web Overall Response Rate Population U. S. military and spouses Quigley et al. (2000) (DoD study) 7,209 83% 27% 37% Civilians c b 45% 58% U.S. Geriatric Chiefs 57 52% Raziano et al. (2001) Zhang (2000) 201 20% 80% 78% Researchers d Schleyer and Forrest (2000) 84% 74% Dentists 4 05 16% NOTE: The multiple Quigley et al. and Raziano et al. entries represent multiple arms of the same study. a This arm of the study used mail as the contact mode. b Includes e-mail. The authors do not distinguish between e-mail and Web as a response mode. c This arm of the study used e-mail as the contact mode. d The response mode in this case was either e-mail or fax. 21,805 Raziano et al. 2001) Sedivi Gaul (2001) and Griffin et al. (2001) (American Community Survey [2000]) Sedivi Gaul (2001) and Griffin et al. (2001) (Library Media Center Survey [1998]) Sedivi Gaul (2001) and Griffin et al. (2001) (Library Media Center Survey [1999]) Quigley et al. (2000) (DoD study) 57 9,596 924 13,440 96% 95% 95% 81% 77% 4% 5% 5% b 77% 38% 38% 63% 42% U. S. Geriatric Chiefs U. S. households Librarians Librarians 19% 23% In Table 2 we see that for most of the studies respondents currently tend to choose mail when given a choice between Web and mail.In fact, even when respondents are contracted electronically it is not axiomatic that they will prefer to respond electronically, as in Raziano et al. (2001) that did not find a statistically significant difference in response rates. Zhang (2000) and Schleyer and Forrest (2000) are the only studies that contradict this conclusion and they tend to represent groups of respondents that are largely or entirely computer literate and comfortable with electronic communication. In comparison, Quigley et al. (2000) and the American Community Survey (2000) study tend to represent general cross-sections of the U. S. ublic in terms of computer literacy and availability and for these studies the fraction that chose Web as the response mode was quite small. In Table 3 we present studies that compared response rates between groups assigned to one of either two or three response modes. Here we see that Internet-based mode response rates generally do not achieve response rates equal to mail surveys. (The table is first ordered from lowest to h ighest e-mail response rate and then by Web response rate. ) Further, Sheehan (2001) concludes that e-mail response rates are declining over time (though the reason for the decline is unknown).Field Methods, Vol. 14 No. 4, 2002 347-367. 5 Table 3. Studies With Multiple Study Arms: Comparing Response Rates for E-mail, Web and Mail Response Modes Total Sample Size 400 500 418 153 262 8,000 904 140 200 1,800 Response Rate E-mail Mail 6% 27% 7% 52% 19% 57% 28% 78% 40% 45% 43% 71% a 58% 53% 68% 38% 34% 72% -54% -62% Population University staff University staff MIS and marketing faculty Health educators BBS newsgroup users Federal employees WSU faculty AT&T employees University staff Businesses in Slovenia Undergraduates at the University 600 of Florida McCabe et al. 2002) 5,000 63% -40% University of Michigan Students — Indicates not applicable; the indicated response mode was not evaluated in the study. a An additional 5 percent that were returned by mail are not included in this number. b In the 2nd follow-up of both study arms respondents were contacted by both mail and e-mail. c An additional phone study arm achieved a response rate of 63%, an additional contact mail / response fax study arm achieved a response rate of 43%. Study Tse et al. (1995) Tse (1998) Schuldt and Totten (1994) Kittleson (1995) Mehta and Sivadas (1995) Couper et al. 1999) Schaefer and Dillman (1998) Parker (1992) Jones and Pitt (1999) c Vehovar et al. (2001) b Pealer et al. (2001) Web ——–19% 32% 58% Parker (1992) is the only study of which we are aware in which e-mail achieved equal or higher response rates when compared to postal mail. Parker conducted a survey of 140 expatriate AT&T employees on matters related corporate policies for expatriation and repatriation, reporting a 63 percent response rate via e-mail (63 returned out of 100 sent by e-mail) compared to a 38 percent response rate for postal mail (14 returned out of 40 sent by mail).Interestingly, Par ker (1992) also attributed the difference in response rates to the fact that, at the time, AT&T employees received a lot of corporate paper junk mail yet, over the internal e-mail system, they received little to no electronic junk mail. Hence, recipients of the paper survey were more likely to discount its importance compared to e-mail survey recipients. With the spread of e-mail â€Å"spam,† this situation is likely to be reversed today.In an example more typical of the current state of affairs, and in one of the few studies to randomize respondents to mode, Couper et al. (1999) obtained an average email response rate of about 43 percent compared to almost 71 percent with mail in a survey of employees in five federal statistical agencies. Couper et al. chose e-mail as the Field Methods, Vol. 14 No. 4, 2002 347-367. 6 mode for the survey over the Web because e-mail was almost universally available in the five agencies while the Web was often not available. Turning to the Web, McCabe et al. 2002) conducted an experiment in which 5,000 University of Michigan students were randomized to receive a survey about drug and alcohol use; 2,500 potential respondents received a mail survey and 2,500 were notified of an equivalent Web-based survey. Respondents in both groups received a $10 gift certificate incentive. In this study, McCabe et al. achieved a 63 percent Web response rate compared to 40% for mail. In contrast, however, Pealer et al. did not find a statistically significant difference between Web and mail response rates for a survey of undergraduates at the University of Florida.The only other published study that achieved exceptional response rates with an Internet-based survey is Walsh et al. (1992) in which potential respondents were solicited by e-mail and offered the option to respond by e-mail or request a paper survey by postal mail. While they did not conduct an equivalent postal mail only survey for comparison (and thus are not listed in Table 3 ), Walsh et al. achieved a 76 percent overall response rate of a randomly sample of subscribers (300 out of a total population of 1,100) to a scientific computer network for an e-mail survey.In addition to providing nonrespondents with two follow-up reminders, a lottery prize of $250 was employed as an incentive. Walsh et al. found that 76 percent of the respondents replied by e-mail and the other 24 percent responded by postal mail. They also received requests from an additional 104 subscribers (who were not chosen in the sample of 300) to participate in the survey. For the self-selected 104, 96 percent responded by e-mail. Not surprisingly, they also found a positive correlation between propensity to respond electronically and amount of network usage.In conclusion, there is little evidence in the literature that Internet-based surveys achieve higher response rates, as a general rule, than conventional surveys. The few Internet-based surveys that have achieved higher response rates have tended to be either of university-based populations or small, specialized populations. The majority of results reported in the literature show Internet-based surveys at best currently achieve response rates equal to conventional modes and often do worse. The reasons for this difference are not yet clear and require more study.Yet, as we have seen, there are also a few examples of Web surveys outperforming mail for some specific populations. Whether this was idiosyncratic of these few surveys, Field Methods, Vol. 14 No. 4, 2002 347-367. 7 or it is an indication that methodology is developing to achieve higher response rates in the new medium is yet to be shown. It is important to note that, contrary to intuition, there is no evidence in the literature that concurrent fielding of a survey via a conventional mode and via an Internet-based mode results in any significant improvement in response rates.This may be because, as Table 2 shows, except in specialized populations, when gi ven a choice between mail and Web surveys, most individuals tend to respond to the mail survey. In addition, there is no evidence that those who would normally refuse to complete a mail survey would choose to respond if the survey was Internet-based. Of course, these results are specific to the current state of the art of Internet-based surveying, existing technology, and the current state of respondent attitudes toward surveys, both Internetbased and conventional.Future developments may significantly alter these findings and more research is certainly warranted in an attempt to improve the response rate performance of Internet-based surveys. Finally, we note that while research surveys based on probabilistic survey sampling methods are generally recognized as being necessary to conduct statistical inference to any population outside of the sample, convenience sampling can also be useful to some researchers for other purposes. For example, early in the course of research, responses from a convenience sample might be useful in developing research hypotheses.Responses from convenience samples might also be useful for identifying issues, defining ranges of alternatives, or collecting other sorts of non-inferential data. In fact, in certain types of qualitative research, convenience samples on the Web may be just as valid as other methods that use convenience samples. There are a number of studies in the literature that used convenience samples, for which response rate comparisons do not apply (and hence precluded their inclusion in Tables 1-3), often with respondents recruited through advertising of some form.While response rates for these studies are meaningless, we present a few of the more interesting studies here to illustrate alternative ways that Web surveys can be used. In a social science study of geographic mobility and other topics Witte et al. (2000) recruit a large number of respondents: 32,688. Similarly, Vehovar et al. (1999) conducted a large-scale survey targeted at the Internet population of Slovenia, which corresponds to about 13 percent of the total population of Slovenia.In both cases, similarly sized traditional mail surveys would likely have been more complicated and very expensive to field. Coomber (1997) conducted a survey about drug dealer practices, where his target population was illicit drug-dealers throughout the world. Coomber solicited responses by e-mail and Field Methods, Vol. 14 No. 4, 2002 347-367. 8 through advertising, and collected responses on the Web hoping his respondents would be encouraged to respond more honestly because of a perceived anonymity.Timeliness In today’s fast-paced world, survey timeliness is increasingly stressed. The length of time it takes to field a survey is a function of the contact, response, and follow-up modes. Decreasing the time in one or more of these parts of the survey process will tend to decrease the overall time in the field. However, it is important to keep in mind that the relevant measure is not average response time but maximum response time (or perhaps some large percentile of the response time distribution) since survey analysis generally does not begin until all of the responses are in.Most studies tend to conclude, often with little or no empirical evidence, that Internet-based surveys are faster than surveys sent by postal mail. This conclusion is usually based on the recognition that electronic mail and other forms of electronic communication can be instantaneously transmitted while postal mail takes more time. However, simply concluding that Internet-based surveys are faster than mail surveys naively ignores the reality that the total amount of time for survey fielding time is more than just the survey response time.A complete comparison must take into account the mode of contact and how long that process will take and the mode of follow-up allowing for multiple follow-up contact periods. For example, if e-mail addresses of res pondents are unavailable and a probability sample is desired then respondents may have to be contacted by mail. In this case a Web survey only saves time for the return delivery of the completed questionnaire, and not for the contact and follow-up, so that the resulting time savings may only be a fraction of the total survey fielding time.In the case of e-mail surveys, where the presumption is that the potential respondents e-mail addresses are known and can therefore be used not just for delivering the survey but also for pre-notification and non-response follow-up, the time savings can be substantial. For example, one is often forced to allow for a week of delivery time in the postal mail. With an advance letter and a single mail follow-up, this one week delay telescopes into over a month in survey fielding when two weeks must be budgeted for initial survey delivery and return time, plus an additional two weeks for a single followup reminder delivery and response time.By compariso n, in an all-electronic process the same operation has the potential to be completed in a few days or less. Yet, even in an all-electronic environment it is not necessarily true that the Internet-based survey will be timelier. For example, in a comparison of response speed Field Methods, Vol. 14 No. 4, 2002 347-367. 9 between e-mail and mail, Tse et al. (1995) did not find a statistically significant difference in the time between sending and receipt of an e-mail survey to university faculty and staff and an equivalent survey sent by mail.Furthermore, to achieve sufficiently high response rates, it may be necessary to leave an Internet-based survey in the field for an extended period of time. For example, a prominent commercial Internet survey company, Knowledge Networks, has indicated that to achieve 70-80 percent response rates they must leave a survey in the field for about 10 days. This period comprises one workweek with two weekends, because they find that most respondents comp lete their surveys on the weekend. However, there are cases in the literature that did show more timely response.Tse (1998) found a statistically significant difference in the average initial response time for those that received an e-mail survey compared to those that received a paper survey in the campus mail (one day versus 2-1/2). Further, in Tse’s experiment, most e-mail survey recipients either responded almost immediately (within one day) or they did not respond at all, which raises the question of the effectiveness of non-response follow-up in the electronic forum. Schaefer and Dillman (1998) also document faster e-mail response rates: 76 percent of all responses were received in 4 days or less. Pealer et al. 2001) found a statistically significant difference in the average return time between their e-mail study arm (7. 3 days) and their mail study arm (9. 8 days). However, the final e-mail survey was received after 24 days and the final mail survey after 25 days†”a negligible difference in overall fielding time. In conclusion, while it is certainly reasonable to conclude prima facie that the delivery time of an Internet-based survey is faster than the delivery of a survey by mail, it does not necessarily follow that the increased delivery speed will translate into a significantly shorter survey fielding period.Two points are relevant: (1) dramatic improvements are only possible with an all-electronic process, which is currently only possible for specialized populations; and, (2) even for populations in which all-electronic surveys are possible, the literature is not very informative as there is no information available about the length of fielding time required to achieve particular response rates. Quality When the primary purpose of a survey is to gather information about a population, the information is useless unless it is accurate and representative of the population.While survey error is commonly characterized in terms of the precisi on of statistical estimates, a good survey design seeks to reduce all types of errors, including coverage, Field Methods, Vol. 14 No. 4, 2002 347-367. 10 sampling, non-response, and measurement errors. (See Groves, 1989, for a detailed discussion of the â€Å"Total Survey Error† approach. ) Indeed, even when a survey is conducted as a census, the results still may be affected by many of these sources of error. Coverage error is the most widely recognized shortcoming of Internet-based surveys.Today the general population coverage for Internet-based surveys still significantly lags behind the coverage achievable using conventional survey modes. However, there are some important caveats to keep in mind. First, the coverage differential is rapidly closing and may become immaterial in the relatively near future (though this is far from a preordained conclusion). Second, even though conventional modes have the ability to reach most of the population, it is becoming increasingly dif ficult to get people to respond (e. g. answering machines are routinely used to screen calls these days and, hence, screen out telephone surveyors and solicitors). Third, while conventional modes have near universal coverage, there will always be special subpopulations that have little or no coverage for any mode. Fourth, in the case of Internetbased surveys, access is only one consideration. Even if the respondent in principle has Internet access (e. g. through a library), there are large portions of the population that are still computer illiterate and would have difficulty correctly responding to such a survey.Finally, access and computer literacy are necessary but not sufficient conditions for success: Respondents must also have compatible hardware and software. However, less than universal access to the Internet can be immaterial for some studies, such as studies that focus on closed populations with equal access or Internet users, for example. In order to improve coverage, Dil lman (2000) recommends a mixedmode strategy for contact, using both e-mail and postal mail for pre-notification. Similarly, using mixed response modes, such as Web and e-mail can be used to increase coverage.However, as we previously mentioned, there is little evidence in the literature that concurrent mixed mode fielding increases response rates over what would have been achieved using a single, conventional mode. In addition to coverage, data quality is a function of a number of other dimensions, including: (1) unit and item nonresponse; (2) honesty of responses, particularly for questions of a sensitive nature; (3) completeness of responses, particularly for openended questions; and, (4) quality of data transcription into an electronic format for analysis if required by the survey mode.All other things held constant (such as pre-notification and non-response followup), unit and item non-response are generally smaller using interviewer-assisted modes (de Leeuw, 1992) compared to s elf-administered survey modes. Face-to-face interviews Field Methods, Vol. 14 No. 4, 2002 347-367. 11 have long been considered the gold standard of surveys and tend to result in the lowest unit and item non-response as well as minimizing respondent misinterpretation of questions and skip patterns.However, it has been shown that interviewer-administered survey modes, particularly face-to-face, yield more socially desirable answers than selfadministered modes (de Leeuw, 1992, Kiesler et al. , 1986, p. 409). This is particularly relevant for surveys of sensitive topics or for surveys that contain sensitive questions, such as questions about income or sexual practices, for example. Mail and other selfadministered modes tend to be the least expensive but often have higher unit and item non-response rates. On the other hand, they tend to elicit the most accurate responses to sensitive questions.Data quality is usually measured by the number of respondents with missing items or the percen tage of missing items. For open-ended questions, longer answers are usually considered more informative and of higher quality. In those studies that compared e-mail versus mail, for closed-ended questions, it appears that e-mail surveys may incur a higher percentage of items missing than mail surveys. As Table 4 shows, for studies in the literature that reported the percentage of missed items, the percentage for mail respondents was less than or equal to the percent for e-mail respondents.Table 4. Average Percentage of Missed Items for E-mail and Postal Mail Surveys Postal Mail Population 14. 2 Undergraduates, University of Florida 0. 7 Business school deans and chairpersons 0. 4 Names and addresses purchased from Internet magazine in the U. K. 0. 5 Fourth-year medical students 0. 8 Employees of five U. S. federal agencies < 0. 3 Active U. S. users of bulletin board system (BBS) news group Study Peale et al (2001) Bachman at al. (1996) Comley (1996)a Paolo et al. (2000) Couper et al . (1999)b Mehta and Sivadas (1995)c a E-mail 14. 2 3. 7 1. 2 1. 2 0. 8 < 0. 3Based on three questions. Based on 81 attitude questions. c Across five different study arms, one of which allowed for both mail and e-mail responses. b At the respondent level, Paolo et al. (2000) also found that 27 percent of e-mail respondents did not respond to at least one question versus 9 percent for mail respondents. Kiesler and Sproull (1986) found the opposite: in the e-mail (contact and response) study arm only 10 percent of respondents failed to complete or spoiled one Field Methods, Vol. 14 No. 4, 2002 347-367. 12 item compared to 22 percent in the mail (contact and response) study arm.Tse (1995, 1998) found no difference in quality of responses. For open-ended questions, studies found that e-mail responses are either longer or of the same length as mail responses. Comley (1996) found that in the two open-ended questions e-mail respondents gave longer answers. One respondent even wrote a minies say. Mehta and Sivadas (1995) found that there was â€Å"hardly any difference between the average completed responses for both the open and close-ended questions† (Mehta and Sivadas, 1995, p. 436). Kiesler and Sproull (1986) found that the total number of words did not significantly differ for e-mail and mail respondents.If one also takes into consideration that open-ended items for mail respondents are not always encoded for cost reasons, it appears that Internet-based survey modes may be better suited to open-ended questions. Other quality issues for Internet-based surveys resulting from some sort of sampling error are generally the same as for conventional surveys. However, as the Internet becomes more ubiquitous, collecting much larger samples becomes more feasible. Indeed, we have talked to some organizations recently that have electronic access to their entire population and are considering eliminating sampling and simply conducting censuses.Often these census efforts result in much larger numbers of respondents than otherwise could have been gathered using traditional survey sampling techniques and those larger numbers give the appearance of greater statistical accuracy. However, such accuracy may be misleading if non-response biases are not accounted for and researchers need to carefully consider the trade-offs between smaller samples that allow for careful non-response follow-up and larger samples with less or no follow-up.The former may have larger standard errors but less bias while the latter may have much smaller standard errors but an unknown, and potentially very large, amount of bias. Finally, we note that Web surveys offer the ability to clearly improve on other forms of self-administered surveys in terms of data validation, skip pattern automation, and the elimination of transcription errors, all of which help to minimize measurement error. Web surveys can be programmed to conduct input validation as a logical check of the respondentà ¢â‚¬â„¢s answers.These types of checks improve data quality and subsequently save time in the preparation of the analysis file. As with logic checks, Web surveys can also be programmed to manage the process of skipping questions. This will eliminate errors and, from the respondent’s point of view, simplify the process of taking the survey. And, while all conventional surveys required some form of conversion into an electronic Field Methods, Vol. 14 No. 4, 2002 347-367. 13 format for analysis, for Web surveys respondents’ answers are directly downloaded into a database, avoiding transcription errors.Cost Designing a survey fundamentally involves making trade-offs between the quality and quantity of data and cost. For smaller research surveys that are not subsidized in any way, a major component of total survey cost is frequently the researchers’ time for survey design and subsequent data analysis. However, these costs vary little by survey mode. A major expense t hat does vary by mode is the labor cost of the personnel who actually execute the survey.Depending on the size of the survey and the complexity of the design, either researcher labor costs, survey personnel labor costs, or a combination of the two will likely dominate the survey budget. Comparing the costs of doing a Web survey versus a mail survey or other some other mode in the literature is difficult because different authors define costs different ways. Academics frequently only consider postage and reproduction costs and often fail to account for the cost of one or more of various types of labor, including: survey design and/or programming, coding, analysis, and other such items.Estimates also vary depending on whether they are given on a per mail-out or per complete survey response basis and, unfortunately, most studies in the literature omit any discussion about costs altogether. However, the question often reduces to how to price the time spent programming a Web survey and w hether and how to price the time of the investigator or a survey coordinator. While lower costs are often touted as one of the benefits of Internet-based surveys, Couper et al. (1999) found no cost benefit in e-mail compared to postal mail surveys in their work.In a large and comprehensive survey effort of different government agencies Couper et al. compared an all e-mail survey (contact, response, and follow-up) versus an all mail survey. They found that evaluating and testing the e-mail software took over 150 hours – almost 4 times as much as they budgeted. For the mail survey, costs for printing and postage were $1. 60 per reply; and data editing and entry cost about $1. 81. For the email survey, managing the e-mail cost $1. 74 per completed case. In addition, they handled over 900 toll-free calls of a mostly technical nature.While the printing and mailing costs were eliminated for the e-mail survey, Couper et al. found that the costs of evaluating and testing the e-mail s oftware, additional post-collection processing, and the costs of maintaining a toll-free phone line which was largely dedicated to responding to technical questions related to the e-mail surveys offset any savings. (For example, while Field Methods, Vol. 14 No. 4, 2002 347-367. 14 the e-mail survey was designed so that respondents would use the reply function of their e-mail program so the resulting replies could be automatically read into a database upon receipt. Further, almost 47 percent of the e-mail surveys required some type of clerical action to prepare them for automatic reading. On the other hand, Raziano et al. (2001) in a small study of 110 Geriatric Chiefs across the U. S. , compute the cost per respondent for their mail study arm to be $7. 70 and for their e-mail study arm $10. 50. The programming time to construct the e-mail survey is factored into this calculation. However, the total programming time accounted for, two hours, may be unrealistic for a large or complica ted survey operation.Also, these estimates fail to reflect the fact that their postal arm response rate from the first mail-out exceeded the e-mail arm response rate after four contact attempts. Hence, for a given desired response rate, the difference in costs would be less as fewer mailings would be required. Similarly, Schleyer and Forrest (2000) in their study received responses over the Web, by mail, and by fax and found the total costs for the Web survey turned out to be 38 percent lower than for the equivalent mail survey. Asch (as reported in Schonlau et al. 2002) found that adding a Web response option to a mail survey to be economical when about 620 responses are obtained over the Web when the Web is first used as the primary survey mode and surveys are only mailed out to non-respondents. Their calculations were based on the trade-off of the expected savings in postage, printing, and labor costs to prepare survey mailing packages and code the subsequent survey returns again st the expected extra costs of programming, additional management effort, and maintaining a telephone help-line for the Web survey.This study did achieve a cost savings since it garnered over 1,000 Web responses. In two studies that essentially ignore personnel costs, Mehta and Sivadas (1995) and Jones and Pitt (1999) conclude, not surprisingly, that Internet-based surveys are less costly than mail surveys. These conclusions simply stem from the fact that Internetbased surveys do not incur postage and printing costs while mail surveys do. In conclusion, when only considering postage and printing costs, e-mail and Web surveys almost by definition are cheaper than mail surveys.However, when the total costs of a survey are considered, including labor and other costs, Web surveys may or may not be cheaper depending on whether the additional expenses incurred with that mode, such as programmer costs, are offset by savings, such as postage and data entry costs. When planning for and subse quently executing a Web survey, care must be taken that unanticipated technical problems are minimized or these problems can easily eliminate all potential cost benefits. Field Methods, Vol. 14 No. 4, 2002 347-367. 15SUMMARIZING THE CURRENT PERFORMANCE OF INTERNET SURVEYS In the Introduction we said that Internet-based surveys are in vogue – those conducted via the Web in particular – primarily because of three assumptions: (a) Web surveys are much cheaper to conduct; (b) Web surveys are faster; and, (c) combined with other survey modes, Web surveys yield a higher response rate than the other survey modes by themselves. That is, the usual naive generalization about Internet-based surveys is that they can be conducted faster, better, cheaper, and easier than surveys conducted via conventional methods.How do these claims stand up when compared to what has been published in the literature? Faster? Web surveys are thought to be much faster than conventional survey modes. W hile there is no question that the delivery time of an Internet-based survey is faster than a survey sent via the mail, there is little to no evidence in the literature to substantiate whether this increase subsequently results in a shorter overall fielding period.We are aware of a couple of organizations that have implemented all-electronic survey processes by communicating with respondents via e-mail, but this is only currently possible for prerecruited panels or specialized subsets of the population. If respondents must be contacted through mail or phone, which generally is the case if a probability sample is required by the research, then there may only be a marginal improvement in overall response times. Better? Response rates for Web surveys where no other survey mode is iven have tended to range from moderate to poor. The reasons for this are not clear. It is possible that potential respondents simply do not respond as well to electronic solicitation or response. If true, thi s may improve as Internet-based communication methods continue to spread and become routine with all segments of the general population. It is also possible that the execution of the Internet-based survey experiments have been less than optimal – something that will improve with surveyor experience.There are a few examples of Web surveys outperforming mail in some of the more recent comparisons between these two media. Whether this was a unique result for these few surveys, or whether it is a leading indicator that the field is maturing and learning how to achieve higher response rates in the new medium is not known. In either case, it Field Methods, Vol. 14 No. 4, 2002 347-367. 16 is of concern that any improvements in these areas may be offset by over-saturation of the population with other forms of commercial surveys.Setting the question of response rate aside, Web surveys offer some advantages over conventional modes. For example, if multi-media and/or interactive graphic s are required then there are few conventional alternatives (and those alternatives, such as face-to-face interviewing, would likely be significantly more costly). If a convenience sample will suffice for the research, then Web can be an excellent medium to use, particularly if the desired respondents are geographically diverse or hard to find/identify.A major issue for Web surveys is their ease of implementation facilitates naive misuse. The particular concern for this medium is the easy collection of large numbers of surveys can result in surveyors and survey data consumers confusing quantity with quality. There is on-going research about the effects of surveying via the Internet, the Web in particular, on unit and item non-response and on the affect the medium has on survey responses. Preliminary results have been reported at some conferences and symposia, but little has appeared in the literature as yet. Cheaper?The usual claim that Web surveys are much cheaper than mail surveys is not necessarily true. Web and e-mail surveys can save on some or all mailing costs, but except for very large surveys these may be small costs in the overall survey effort. Web surveys can also eliminate data entry costs; e-mail survey results may not because they often require additional manipulation before they can be downloaded into an analytical database. However, savings in data entry may be partially or completely offset against higher programming costs and additional help desk staffing requirements.The literature mostly neglects labor costs, which form the highest cost component for Web surveys. Nonetheless, adding a Web survey to a mail survey can be cost efficient if done carefully and properly. Easier? The implementation of Web surveys is technically more involved than mail or phone surveys. Survey designers need to specify many issues related to the technical control of Web surveys (e. g. how to move back and forward between questions, input validation, passwords, for what questions answers are not optional) that are simpler or not required with conventional survey modes.Web surveys also require more extensive Field Methods, Vol. 14 No. 4, 2002 347-367. 17 pretesting to ensure both that the questions elicit the desired information and that the program works properly across numerous hardware and software configurations. The fielding process may or may not be made easier. Internet-based surveys have the potential to eliminate some of the more labor-intensive fielding tasks, such as survey package preparation and mailing and the subsequent data entry.Yet, if mixed modes are required to obtain sufficient population coverage and/or response rates, then these tasks cannot be completely eliminated and the fielding process may actually then become more complex since support for two or modes must be maintained and managed. What is the Future of Internet-based Surveying? The first Internet browser was introduced only about a decade ago and early use of th e World Wide Web as a survey medium only started about five years ago. The result is that significant research results about the use of this new survey medium have only recently begun to become available in the literature.Hence, there is a great deal that is still not well known about Internet-based surveys. While some predict that Web surveys will replace other survey modes, we expect Web surveys to develop into a distinct survey mode with advantages and disadvantages that will have to be weighed against the conventional alternatives. Little is known about Web instrument design and the effects of instrument design on how survey participants respond to a survey or a particular survey question, and what enhances response rates and response accuracy.For example, at the 2001 American Association of Public Opinion Researchers conference, some anecdotal evidence was presented that respondents taking surveys on the Web had shorter attention spans, tending to browse the survey like they br owse other Web sites. If true, this would suggest that long surveys and/or surveys with complex questions may not perform as well on the Web as by mail. While many of the design principles from paper-based surveys may translate to Internet-based surveys, much more research is required.To date, most Web surveys have been conducted on convenience samples or in organizations where a list of target populations readily exists. However, Internet-based surveys with probability samples can be fielded by using the mail or telephone for respondent contact and the Web for response. There is currently no equivalent to random digit dialing for e-mail. Even though the fraction of the population having access to email will continue to grow, it is unlikely that one will ever be able to construct a random e-mail address in the same way a random telephone number is constructed.However, Field Methods, Vol. 14 No. 4, 2002 347-367. 18 large commercial e-mail lists may yet emerge that are of high enough quality to be useful in survey research. A major challenge for researchers will be to distinguish themselves and their survey from the plethora of commercial and entertainment surveys that exist and continue to multiply on the Web. These other surveys will continue to proliferate because the financial and technical barriers are so low for Web surveys. Thus, just as telephone survey response rates have continued to decline because of telemarketers, it s likely to become increasingly difficult to achieve superior response rates in the new medium. Nonetheless, Internet-based surveys are here to stay. The challenge for researchers is to learn to use the new medium to their best advantage. REFERENCES Asch, B. , (2001). RAND, Santa Monica, California. Personal communication. Bachman, E. , J. Elfrink, and G. Vazzana (1996). Tracking the Progress of E-Mail vs. Snail-Mail, Marketing Research, 8, 31-35. Bradley, N. (1999). Sampling for Internet Surveys. An Examination of Respondent Selection for Internet Research, Journal of the Market Research Society, 41, 387395.Cochran, W. G. (1977). Sampling Techniques, 3rd edition, John Wiley & Sons, New York, NY. Comley, P. (1996). Internet Surveys. The Use of the Internet as a Data Collection Method, ESOMAR/EMAC: Research Methodologies for â€Å"The New Marketing,† Symposium ESOMAR Publication Services, vol. 204, 335-346. Coomber, R. (1997). Using the Internet for Survey Research, Sociological Research Online, 2, 14-23. Couper, M. (2000). Web Surveys, A Review of Issues and Approaches, Public Opinion Quarterly, 64, 464-494. Couper, M. P. , J. Blair and T. Triplett (1999). A Comparison of Mail and E-mail for a Survey of Employees in U.S. Statistical Agencies. Journal of Official Statistics, 15, 39-56. Couper, M. P. , M. W. Traugott, M. J. Lamias (2001). Web Survey Design and Administration. Public Opinion Quarterly, 65, 230-253. Field Methods, Vol. 14 No. 4, 2002 347-367. 19 de Leeuw, E. D. (1992). Data Quality in Mail, Tel ephone, and face to Face Surveys, Ph. D. dissertation, University of Amsterdam, ISBN 90-801073-1-X. Dillman, D. A. (2000). Mail and Internet Surveys, The Tailored Design Method, 2nd ed. , John Wiley & Sons, New York, NY. Dillman, D. A. , R. D. Tortora, J. Conradt and D. Bowerk (1998). Influence of Plain vs.Fancy Design on Response Rates for Web Surveys. Unpublished paper presented at the Annual Meeting of the American Statistical Association, Dallas, TX. Dillman, D. A. (1978). Mail and Telephone Surveys, The Total Design Method, John Wiley & Sons, New York, NY. Everingham, S. (2001). RAND, Santa Monica, California. Personal communication. Fowler, Jr. , F. J. (1993). Survey Research Methods, 2nd ed. , Applied Social Science Research Methods Series, volume 1, SAGE Publications, Newbury Park, CA. Griffin, D. H. , D. P. Fischer, and M. T. Morgan (2001). Testing an Internet Response Option for the American Community Survey.Paper presented at the American Association for Public Opinion Re search, Montreal, Quebec, Canada. Groves, R. (1989). Survey Errors and Survey Costs, John Wiley & Sons, New York, NY. Hamilton, C. H. (2001). Air Force Personnel Center, Randolph Air Force Base, personal communication. Henry, G. T. (1990). Practical Sampling, Applied Social Research Methods Series, Volume 21, SAGE Publications, Newbury Park, CA. Jones, R. and N. Pitt (1999). Health Surveys in the Workplace: Comparison of Postal, Email and World Wide Web Methods, Occupational Medicine, 49, 556-558. Kiesler, S. and L. S. Sproull (1986).Response Effects in the Electronic Survey, Public Opinion Quarterly, 50, 402-413. Kish, L. (1965). Survey Sampling, John Wiley and Sons, New York, NY. Kittleson, M. J. (1995). An Assessment of the Response Rate Via the Postal Service and E-Mail, Health Values, 18, 27-29. McCabe, S. E. , Boyd, C. , Couper, M. P. , Crawford, S. , and H. d'Arcy (2002). Mode Effects for Collecting Health Data from College Students: Internet and US Mail. Paper under review. Mehta, R. and E. Sivadas (1995). Comparing Response Rates and Response Content in Mail versus Electronic Mail Surveys, Journal of the Market Research Society, 37, 429-439.Field Methods, Vol. 14 No. 4, 2002 347-367. 20 Nichols, E. , and B. Sedivi (1998). Economic Data Collection via the Web: A Census Bureau Case Study Proceedings of the Section On Survey research Methods, American Statistical Association,366-371. Paolo, A. M. , Bonaminio, G. A. , Gibson, C. , Partridge, T. and K. Kallail (2000). Response Rate Comparisons of e-mail and mail distributed student evaluations, Teaching and Learning in Medicine, 12, 81-84. Parker, L. (1992). Collecting Data the E-Mail Way, Training and Development, July, 5254. Pealer, L. , R. M. Weiler, R. M. Pigg, D.Miller, and S. M. Dorman (2001). The Feasibility of a Web-Based Surveillance System to Collect Health Risk Behavior Data From College Students. Health Education & Behavior, 28, 547-559. Quigley, B. , Riemer, R. A. , Cruzen, D. E. , and S. Rose n (2000). Internet Versus Paper Survey Administration: Preliminary Finding on Response Rates, 42nd Annual Conference of the International Military Testing Association, Edinburgh Scotland. Raziano, D. B. , R. Jayadevappa, D. Valenzula, M. Weiner, and R. Lavizzo-Mourey (2001). E-mail Versus Conventional Postal Mail Survey of Geriatric Chiefs.The Gerontologist, 41, 799-804. Schaefer, D. R. and D. A. Dillman (1998). Development of a Standard E-mail Methodology: Results of an Experiment. Public Opinion Quarterly, 62, 378-397. Schleyer, T. K. L. and J. L. Forrest (2000). Methods for the Design and Administration Web-Based Surveys, Journal of the American Medical Informatics Association, 7, 416-425 Schillewaert, N. , F. Langerak and T. Duhamel (1998). Non-probability Sampling for WWW Surveys: A Comparison of Methods, Journal of the Market Research Society, 40, 307-322. Schonlau, M. , Fricker, R. D. , Jr. , and M.Elliott. (2002). Conducting Research Surveys via E-Mail and the Web, RAND: San ta Monica, MR-1480-RC. Schuldt, B. A. and J. W. Totten (1994). Electronic Mail vs. Mail Survey Response Rates, Marketing Research, 6, 36-44. Sedivi Gaul, B. (2001a). Web Computerized Self-administered Questionnaires (CSAQ). Presentation to the 2001 Federal CASIC Workshops. U. S. Census Bureau, Computer Assisted Survey Research Office. Sedivi Gaul, B. (2001b). United States Census Bureau, Washington, D. C. Personal Communication. Field Methods, Vol. 14 No. 4, 2002 347-367. 21 Sheehan, K. B. (2001).E-mail survey response rates: A review. Journal of ComputerMediated Communication, 6(2). Retrieved March 9, 2002, from http://www. ascusc. org/jcmc/vol6/issue2/sheehan. html. Tse, A. C. B. , Tse, K. C. , Yin, C. H. , Ting, C. B. , Yi, K. W. , Yee, K. P. , and W. C. Hong (1995). Comparing Two Methods of Sending Out Questionnaires: E-mail versus Mail, Journal of the Market Research Society, 37, 441-446. Tse, A. C. B. (1998). Comparing the Response Rate, Response Speed and Response Quality of Two Methods of Sending Questionnaires: E-mail versus Mail, Journal of the Market Research Society, 40, 353-361.Tuten, T. L. , D. J. Urban, and M. Bosnjak (in press, 2002). â€Å"Internet Surveys and Data Quality: A Review† in: B. Batinic, U. Reips, M. Bosnjak, A. Werner, eds. , Online Social Sciences, Hogrefe & Huber, Seattle, 7-27. Vehovar, V. , K. Lozar Manfreda, and Z. Batagelj (1999). Web Surveys: Can the Weighting Solve the Problem? Proceedings of the Section on Survey Research Methods, American Statistical Association, Alexandria, VA, 962-967. Vehovar, V. , K. Lozar Manfreda, and Z. Batagelj (2001). Sensitivity of e-commerce Measurement to the Survey Instrument.International Journal of Electronic Commerce, 6, 31-51. Walsh, J. P. , S. Kiesler, L. S. Sproull, and B. W. Hesse (1992). Self-Selected and Randomly Selected Respondents in a Computer Network Survey, Public Opinion Quarterly, 56, 241-244. Witte, J. C. , L. M. Amoroso, and P. E. N. Howard (2000). Research Methodol ogy – Method and Representation in Internet-based Survey Tools, Social Science Computer Review, 18, 179-195. Zhang, Y. (2000). Using the Internet for Survey Research: A Case Study, Journal of Education for Library and Information Science, 5, 57-68. Ron Fricker is a statistician at RAND.He has designed, managed, and analyzed many large surveys of national importance, including a survey of Persian Gulf War veterans about Gulf War Illnesses and, most recently, a survey on domestic terrorism preparedness in the United States. Dr. Fricker holds Ph. D. in Statistics from Yale University. In addition to his position at RAND, Dr. Fricker is the vice-chairman of the Committee on Statisticians in Defense and National Security of the American Statistical Association, an associate editor of Naval Research Logistics, and an adjunct assistant professor at University of Southern California.Field Methods, Vol. 14 No. 4, 2002 347-367. 22 Matthias Schonlau, Ph. D. , is an associate statisticia n with RAND and heads its statistical consulting service. Dr. Schonlau has extensive experience with the design and analysis of surveys in areas such as health care, military manpower and terrorism. Prior to joining RAND, he held positions with the National Institute of Statistical Sciences and with AT Labs Research. Dr. Schonlau has co-authored numerous articles as well as a recentRAND book â€Å"Conducting Internet Surveys via E-mail and the Web. † In 2001, he and his team won second place in the data mining competition at the world's largest conference on data mining â€Å"KDD. † Acknowledgements. The helpful and substantive comments of three anonymous reviewers and the editor significantly improved this work. Our research was supported by RAND as part of its continuing program of independent research. Field Methods, Vol. 14 No. 4, 2002 347-367. 23

Types of Entrepreneurship

Types of Entrepreneurship and Economic Growth DOI:10. 1093/acprof:oso/9780199596515. 003. 0004 Abstract and Keywords This chapter is an empirical exploration of types of entrepreneurship and their impact on economic growth in developing and transition countries. It relates indicators of entrepreneurship to average rates of economic growth in the period 2002–5. For this the chapter utilizes a dataset on entrepreneurship in thirty? six countries from the Global Enterprise Monitor (GEM), collected in 2002.It finds that indicators of young business activity have a significant impact on growth in high? income countries and transition countries, but not in developing countries. The chapter explains the lack of significant effects in developing countries by pointing to the lack of complementary physical and human capital and the scarcity of larger companies that can act as a training ground for SMEs. Keywords:  Ã‚  Ã‚  entrepreneurship,  growth? oriented entrepreneurship,  econ omic growth,  global entrepreneurship monitor 4. 1  IntroductionEntrepreneurship has long been considered a crucial mechanism of economic development (Schumpeter  1934; Landes  1998). However, empirical studies on the role of entrepreneurship in economic growth show mixed evidence (Stam  2008). This is not remarkable because there is much heterogeneity in both the kinds of entrepreneurship and the kinds of economic contexts in which economic growth takes place. Until now studies have not sufficiently accounted for this heterogeneity on the micro- and macro-level, which limits our insight into the contingent role of entrepreneurship in economic growth.Important questions in this respect are: ‘How does the role of entrepreneurship differ between high-income, transition, and medium-income countries? ’, and ‘What kinds of entrepreneurship are most crucial for economic growth? ’. The objective of this chapter is to provide insights into the role of dif ferent types of entrepreneurship in economic growth, and on how this role differs in poor and rich economies. In this chapter, we empirically investigate the effect of entrepreneurship on economic growth at the country-level.We use data from the Global Entrepreneurship Monitor (GEM), which provides comparative data on entrepreneurship from a wide range of countries. An important element of this chapter is that we compare the effects of entrepreneurial activity on economic growth in high-income countries, transition countries (China, Hungary, Poland, Russia, and Slovenia), and medium-income countries (Argentina, Brazil, Chile, India, Mexico, South Africa, and Thailand). This dataset also enables us to make a distinction between the effects of entrepreneurship in general and  (p. 9 )growth-oriented entrepreneurship in particular. We present empirical tests of the impact of entrepreneurial activity on GDP growth over a four-year period for a sample of 36 countries. Our empirical anal yses suggest that entrepreneurship does not have an effect on economic growth in medium-income countries, in contrast to transition and high-income countries where especially growth-oriented entrepreneurship seems to contribute strongly to macroeconomic growth. 4. 2  Entrepreneurship and economic development Development is a broad concept entailing the raising of human capabilities (Sen  1999).One of the central challenges in improving economic development is to increase the standards of living for individuals and growth of the economy as a whole. Even though economic growth in itself is a rather narrow target, it is probably one of the most important targets for development policies. It is also one of the measures that is most easy to access for analysts, and probably the best measure to make cross-national (Barro  1991; Sala-i-Martin  1997) and historical (Maddison  2001) analyses of the development of economies.Traditionally the economic output of a country is seen as a function of capital and labour inputs, combined with technical change (Solow  1957). Of course, conflicts and wars might interrupt this function (Sala-i-Martin  1997), but these are ‘just’ contingencies. The standard production function used shows that economic output (Y) is a function of the sum of labour and capital inputs, and the level of technological knowledge (i. e. productivity). This means that economic growth—the growth of economic output—is a function of the growth of labour and capital inputs and technological progress.In traditional models of economic growth investment in capital, labour, and technology is sufficient to realize economic growth. New models of economic growth see these investments as a necessary complement to entrepreneurship/innovation, but not as a sufficient explanation for economic growth in its own right (Nelson and Pack  1999). One could even argue that high rates of investment in human and physical capital are them selves stimulated by effective innovation, and cannot be maintained in the absence of innovation.Recent studies emphasize entrepreneurship as a driver of economic development and some authors include entrepreneurship as a fourth production factor in the macroeconomic production function (Audretsch and Keilbach  2004). Entrepreneurship is the factor that creates wealth by combining existing production factors in new ways. Entrepreneurs experiment with new combinations of which the outcomes are uncertain, but in order to make progress, many new variations have to be tried in order to find out which ones will  (p. 80 )  improve (economic) life (Rosenberg and Birdzell  1986).Other authors have argued that entrepreneurship will only unlock economic development if a proper institutional setting is in place (Baumol  1990; Boettke and Coyne  2003; Powell  2008). This institutional setting comprises informal as well as formal institutions (North  1990). An essential formal in stitution for welfare enhancing entrepreneurship is property rights. Insecure property rights have been an important constraint on the investments by entrepreneurs in transition countries, even more so than capital market constraints (Johnson, McMillan, and Woodruff  2000).A specific example regarding property rights is the fact that until 1988 private firms with more than seven workers were not even allowed to operate legally in China (Dorn  2008). One might say that the production factors capital, labour, technology, and entrepreneurship are the proximate causes of economic development, while institutions are a fundamental cause of economic development (Acemoglu, Johnson, and Robinson  2004). Next to productivity growth and technological change in established sectors, the development process in less advanced countries is largely about structural change (Gries and Naude  2010; Nelson and Pack1999; Rodrik  2007).It is a process in which an economy finds out—self-dis covers—what it can be good at producing, out of the many products that already exist. The role of entrepreneurs in developing countries does not equal innovation and R&D as commonly understood in advanced economies. Their role is to discover that a certain good, already well-established in world markets, can be produced at home at low cost (Hausmann and Rodrik  2003; Rodrik  2007).   Examples of this are the entrepreneurs that figured out that Bangladesh was good in the production of T-shirts, Colombia in cut flowers, India in software services, and Taiwan in bicycles and display technologies. Even if entrepreneurs cannot appropriate all these gains for themselves, their discoveries generate large social gains for their economies. Spurring entrepreneurs to invest in their home economy is said to be one of the most important aspects of stimulating growth in poor countries (Rodrik  2007). Investing refers here to innovation (e. g. mploying new technology, producing new products, searching for new markets) and expanding capacity. These investments trigger the combination of capital investment and technological change. In advanced capitalist economies, innovation and structural change take place through the combined efforts of small (independent inventors) and large innovative (organized R&D) firms, which complement each other in changing the economy (Nooteboom  1994; Baumol  2002). In developing countries the role of large firms is relatively small (Ghoshal, Hahn, and Moran  1999).In transition countries there are relatively many large organizations but these are largely in a process of restructuring and dismantling. This means that  (p. 81 )  small firms will be the prime movers in the process of structural change in developing and transition economies. We expect that the level of growth-oriented entrepreneurship in a country is a more relevant driver of economic growth than the mostly used indicators of entrepreneurship like self-employ ment and new firm formation.In contrast to rich countries, entrepreneurship in medium-income countries is mainly driven by necessity (Bosma et al. 2008). 2  Most entrepreneurs in these economies do not start a firm because they desire independence or because they want to increase their income as compared to being an employee, which are the dominant motives in rich countries. Most new businesses in medium-income countries are started out of necessity, in contrast to high-income countries, where entrepreneurship is most often opportunity-driven.This is reflected in the finding that in poor countries self-employed persons are less happy than employees, while the reverse is true in high-income countries (Blanchflower and Oswald  1998; Graham  2005). Entrepreneurs in medium-income countries most often start a business because they have no other way of earning a living. These entrepreneurs are not likely to be involved in a process of self-discovery; their actions are not likely to have an effect on the restructuring and diversification of the poor economies (Rodrik  2007). . 3  Data and research methods It is generally acknowledged that there are differences in the distribution of entrepreneurship across countries. Studies exploring differences in entrepreneurship across countries often focus on the incidence of new firm registration or self-employment, which may not be reliable indicators when applied to transition and developing countries with significant informal economies and fewer alternatives to self-employment.For these reasons we have used the Young Business (YB) indicator, defined as the percentage of adult population that is the owner/manager of a business that is less than 42 months old. Many studies have used the total entrepreneurial activity index, but that also includes the more speculative category of nascent entrepreneurs (individuals preparing a new business). In the current study we investigate whether the presence of growth-oriented en trepreneurs is a more important determinant of national economic growth than entrepreneurial activity in general.We will perform regression analyses with the YB  high-growth expectation  rate and the YB  medium-growth expectation  rate as independent variables and compare their impact on economic growth with the impact of the general YB index. The data and model used in this study are described below. We use a sample of 36 countries participating in the GEM in 2002. Data on six basic variables are used in our model: YB rate, YB medium-growth, YB  (p. 82 )  high-growth, growth of GDP, per capita income, and the growth competitiveness index (GCI). YB indexYB is defined as the percentage of adult population that is owner/manager of a business that is less than 42 months old. The YB high-(medium) growth expectation rate is defined as the percentage of adult population that is owner/manager of a business that is less than 42 months old,  and expects to employ 20 (six) emplo yees or more within five years  (YB6 and YB20). The YB medium-growth rate has some similarity to the entrepreneurship indicator used by Djankov et al. (2006), which includes owner-managers of a business with five or more employees. Data on the YB rate are taken from the GEM Adult Population Survey for 2002.Growth of GDP (? GDP) (Real) GDP growth rates are taken from the IMF World Economic Outlook database of the International Monetary Fund from September 2005. In equations (1) and (2) below variable ? GDPit  refers to the period 2002–5 (average annual growth) while the lagged GDP growth variable (? GDPi,t-1) refers to the period 1998–2001. Per capita income (GNIC) Most studies on GDP growth include the initial level of income in their analysis and find it to be significant (the conditional convergence effect, cf. Abramovitz  1986). Gross national income per capita 2001 is expressed in (thousands of) PPP dollars.These data are taken from the 2002 World Development Indicators database of the World Bank. Growth Competitiveness Index (GCI) In order to cover some aspects of the state of technology and institutions in a country (see Section  4. 2) we used the GCI for the year 2001 of the World Economic Forum (see McArthur and Sachs  2002). Given the low number of observations we are forced to use a combined index in our model. Even though there are huge problems in measuring technological capabilities and institutions (see Lall2001), the composite GCI is probably the best combined index available that covers these two factors simultaneously. p. 83 )  We investigate whether (growth-oriented) entrepreneurship may be considered as a determinant of economic growth, alongside the well-known determinants technology, institutions, and the macroeconomic environment, which are captured by the GCI. As both entrepreneurship and the factors underlying the GCI are assumed to be structural characteristics of an economy, we do not want to explain short-te rm economic growth but rather growth in the medium-term. Therefore we choose average annual growth over a period of four years (2002–5) as the dependent variable in this study.Following van Stel, Carree, and Thurik (2005), we use (the log of) initial income-level of countries to correct for catch-up effects, and lagged growth of GDP to correct for reversed causality effects, as additional control variables. 3 We allow for the possibility of different effects for high-income, transition, and medium-income countries. In addition we also test whether the effect of YB is different for transition countries. 4  YB rates may reflect different types of entrepreneurs in countries with different development levels, implying different impacts on growth.This is tested by defining separate YB variables for different groups of countries (high-income, transition, and medium-income countries). Our model is represented by equations (1) and (2). These equations are estimated separately by or dinary least squares. The expectation that growth-oriented YBs contribute more to national economic growth than YBs in general corresponds to b2  (c2) being larger than b1  (c1). In these equations sub-scripts t and t-1 loosely indicate that the independent variables are measured prior to the dependent variable.The exact years and periods for which the variables are measured can be found in the variable description above. ?GDPit=a+b1YBrichi,t? 1+c1YBtransitioni,t? 1+d1YBpoori,t? 1 +e? log(GNICi,t? 1)+f? GCIi,t? 1+g GDPi,t? 1+? it (1) ?GDPit=a+b2YB_high-growthrichi,t? 1+c2YB_high-growthtransitioni,t? 1+d2YB_high-growthpoori,t? 1+e? log(GNICi,t? 1)+f? GCIi,t? 1+g GDPi,t? 1+? it (2) To illustrate the data at hand, Table  4. 1  provides the YB rates and the YB medium- and high-growth rates in 2002 as well as the average annual growth rates of GDP over the period 2002–5.From Table  4. 1  and Figures  4. 1  and  4. 2  it can be seen that the ranking of countries in terms of YB or YB high-growth may be quite different. For instance, while China ranks fifth in terms of YB, it ranks first in terms of  (p. 84 ) Table 4. 1 Young business rates (2002) and GDP growth rates for 36 countrieshigh-growth YB. In contrast, Thailand ranks third in terms of YB, but only tenth in terms of high-growth YB. Figure 4. 1  Young business rates Figure 4. 2  Young business 20 rates Figure 4. 3  Correlation of young business rates and GDP growth rates Figure 4.   Correlation of high growth-oriented young business rates (20+) and GDP growth rates When we regress the rate of GDP growth on the YB rate and the YB20 rate, the YB20 rate reveals to have a stronger correlation with GDP growth (see Figures  4. 3  and  4. 4). (p. 85 )(p. 86 ) 4. 4  Entrepreneurship and national economic growth 4. 4. 1  Regression analyses The results of our empirical exercises are in Table  4. 2. Model I presents the regression results of the impact of the general YB i ndex (see equation (1)), while Models II and III show the results using the YB6 and YB20 rates as main independent variables (see equation (2)).The results presented in Table  4. 2  show that the impact of entrepreneurial activity is significantly positive for rich countries, but effectively zero for poor countries. The presence of growth-oriented entrepreneurs seems to be more important for achieving GDP growth than general entrepreneurship. Comparing the coefficients of the various YB rates, we see that the impact of YB6 is greater when compared to the impact of YB in general. Meanwhile the impact of YB20 is even greater, but not always statistically significant. Having more growth-oriented entrepreneurs seems to be particularly important in transition countries.Both the magnitude and the statistical significance of the estimated coefficient point to a stronger impact compared to high-income or medium-income countries. There are many reasons that could(p. 87 ) Table 4. 2 Regre ssion models average annual growth of GDP over the period 2002–5 (N=36)explain the importance of growth-oriented entrepreneurs in transition countries (Smallbone and Welter  2006). First, there are many entrepreneurial opportunities in formerly state-dominated sectors. Second, many highly qualified individuals lost their jobs at state-financed organizations (e. . universities, enterprises, government services). Third, there are many highly qualified (potential) entrepreneurs in these countries (especially in Eastern European countries), who do not face the opportunity costs of working for large public or private organizations. Fourth, those highly qualified (potential) entrepreneurs are also well connected to the power networks that were, and to a large extent still are, important in the political and economic arena of these countries, which takes away some barriers for high-growth firms in these countries.Summarizing, it may be argued that in transition economies high-grow th opportunities are more widely available and hence, a higher number of growth-oriented entrepreneurs willing to act on these opportunities may be particularly fruitful for achieving growth in these countries. However, we should be aware of the large diversity in the group of transition countries, which comprises countries like Russia and China, as well as Hungary and Slovenia. (p. 88 )  Our regression results should be interpreted with care as the analysis is based on a limited number of observations (36 countries).As a test of robustness we estimated the models leaving out one country at a time, i. e. we computed 36 auxiliary regressions, where each regression uses 35 observations (each time leaving one of the 36 countries out). Although t-values sometimes dropped a little, coefficients and t-values were generally in line with those reported in Table  4. 2. The country that matters the most for the results obtained in Table  4. 2  is China. This is not surprising as China combines high YB/YB6/YB20 rates with high GDP growth rates (see Table  4. 1). When leaving this country out of the sample, the coefficient (t-value) for the transition countries is 0. 2 (0. 5) for the YB rate, 1. 47 (1. 2) for the YB6 rate, and 1. 72 (1. 1) for the YB20 rate. The low t-values are in part due to the low number of observations. Note, however, that the coefficients are very similar to the full sample estimates reported in Table  4. 2. Furthermore, the Jarque–Bera test on the normality of disturbances is passed for all models reported in Table  4. 2, indicating that it is not necessary to remove individual country observations. Therefore we feel that our results are quite robust to the potential influence of outliers.Nevertheless, given the low number of observations, the results should only be seen as a first illustration of how the impact of different types of entrepreneurship may differ between groups of countries with different levels of development. 4 . 4. 2  Medium-income countries Within the groups of transition and developing economies there are substantial differences in entrepreneurship rates. Chile stands out because of a particularly high rate of growth-oriented entrepreneurship, while Mexico has a particularly low rate of growth-oriented entrepreneurship.In contrast to high-income countries, entrepreneurship in medium-income countries is mainly driven by necessity: self-employment is often the only occupational choice given a paucity of other sources of employment (necessity-based entrepreneurship; see Acs and Amoros  2008; Bosma et al. 2008). The actions of most of the entrepreneurs in medium-income countries are not likely to have an effect on the restructuring and diversification of the poor economies. This would be the whole story if the rates of growth-oriented entrepreneurship would also be marginal in these economies.This is only the case for Mexico. Next to Chile—where opportunity-driven entrepreneurshi p is dominant—Brazil, India, and Argentina perform quite well with respect to growth-oriented entrepreneurship. This means that there still is a substantial group of entrepreneurs in medium-income countries that might get involved in a process of self-discovery. The problem in practice is that in contrast to rich and transition economies, growth-oriented entrepreneurship is less likely to  (p. 89 )  be realized in developing economies, due to constraints on the provision of capital and (skilled) labour.An additional constraint in medium-income countries is that there are relatively few (foreign) large companies, which could act as a training ground for prospective growth-oriented entrepreneurs, and could open up distribution channels for new fledgling enterprises (Knorringa  1996). This is also reflected in the finding of Bosma, Stam, and Wennekers (2010) that the incidence of intrapreneurship (i. e. employees developing new business activities for their employer) is mu ch lower in medium-income countries than in high-income countries.In addition, one should make a distinction between large firms with productive (manufacturing) and resource extractive (mining, oil) activities here, as the former will be more useful for the development of entrepreneurship than the latter. 4. 4. 3  Transition countries New firms in transition countries not only displace obsolete incumbents but also fill in new markets, which were either non-existent or poorly populated in the past. Our study suggests that in transition countries, growth-oriented entrepreneurs make an important contribution to economic growth.They create new jobs with relatively high incomes which the small incumbent population of private firms cannot provide. This entrepreneurial growth process is facilitated by the relatively high levels of human capital in combination with relatively low opportunity costs of self-employment of the adult population. The high degree of environmental dynamism in the se countries—which is likely to positively affect the level of growth expectations and realizations of entrepreneurs in these countries—requires ambitious and well-connected entrepreneurs in order to translate these abundant opportunities in economic growth.There are considerable differences within the group of transition countries. Hsu (2005) shows that the role of these connections differs considerably between China and Russia: in China it was a tool which could be used to build enough trust to allow business transactions to succeed (‘capitalism without contracts’). In contrast, in Russia these connections devolved into corruption, and faded in importance for ordinary citizens. Without a way to build trust or extend networks, Russians retreated into defensive involution, and engaged in predatory behaviour against those outside their small circles of friends.Instead of capitalism without contracts, Russia suffered the depredations of ‘capitalists wi thout capitalism’. There are also substantial differences in entrepreneurship rates within the groups of transition economies. China stands out because of particularly high rates of growth-oriented entrepreneurship (cf. Hsu  2005). Even though the YB  (p. 90 )  rate is below the average of transition countries, the growth of self-employment has been enormous, not only in the richer coastal provinces, but also in rural areas (Mohapatra, Rozelle, and Goodhue  2007).Research by Djankov et al. (2006) also shows that entrepreneurs in China are more risk-taking and more committed to an entrepreneurial career than entrepreneurs in Russia. In addition, Russia has (and had: see Hsu  2005) a particularly low rate of entrepreneurship in general as well. The striking difference between entrepreneurship rates in China and Russia can be explained by their different paths from socialism to capitalism: gradualism and a shock therapy (see Burawoy  1996).In China the gradual transf ormation started with a policy of decollectivization (decentralization of property relations) in the late 1970s and the promotion of small-scale industry, with a focus on promoting independent entrepreneurship. Experimentation with new economic arrangements, for example privatization of small state-owned enterprises, has led to a favourable accumulation of productive capabilities in China. In contrast, Russia underwent a shock therapy in which the old communist regime was liquidated, with a focus on rapid privatization of the state sector.However, the Russian state failed to organize a market economy, which led to a coordination and entrepreneurial vacuum into which have stepped conglomerates, banks and mafia, siphoning off surplus from production to exchange (Burawoy  1996). 4. 5  Discussion of policy implications In this section we will briefly discuss the potential implications of our exploration of the relationship between types of entrepreneurship and economic growth for en trepreneurship policy and industrial/cluster policy in medium-income and transition countries. 5 4. 5. 1  Entrepreneurship policyOur empirical analyses suggest that entrepreneurship does not have an effect on economic growth in medium-income countries, in contrast to transition and high-income countries where both growth-oriented entrepreneurship and entrepreneurship in general seem to contribute strongly to macroeconomic growth. Does this mean that stimulating entrepreneurship in medium-income countries is bad policy? The least we can say is that stimulating entrepreneurship alone will be insufficient as it is likely to attract necessity entrepreneurs with low human capital levels who do not contribute to economic growth.The non-significant effect of entrepreneurship on economic growth in medium-income countries might point at a shortage of large firms in these countries. By exploitation of economies of scale and scope and by  (p. 91 )  adopting and diffusing technology devel oped elsewhere, large firms are important in transforming a developing economy into a developed economy (van Stel, Carree, and Thurik  2005). In these economies local workers are more productive working as wage employees than as entrepreneurs. Nevertheless stimulating growth-oriented entrepreneurship might be an additional element of transforming a developing economy into a developed one.Attracting investments by large (possibly foreign) firms, stimulating growth-oriented entrepreneurship, investing in labour and capital, and improving the institutional framework may be the recipe for growth here. On the one hand this is old news, in that it provides a plea for the traditional role of governments to invest in education and physical infrastructure, and to build and maintain a set of institutions that enable the development of the private sector (cf. Rosenberg and Birdzell  1986). On the other hand, the addition of growth-oriented entrepreneurship in development policy for medium- income and transition countries is a new element.One must be careful to target the right group of entrepreneurs though, i. e. governments should avoid that resources made available through government stimulation programmes are absorbed by necessity entrepreneurs with low human capital levels. 4. 5. 2  Industrial/cluster policy The focus of this chapter has been on the country-level, which disregards the sub-national level of analysis, and what is of particular relevance here, the level of regional clusters (regional concentrations of particular industries). These regional clusters have proved to be important drivers of economic development in, for example, Taiwan, India, and Brazil.These clusters are both driven by and drive growth-oriented entrepreneurship. Growth-oriented entrepreneurs that start to invest in a particular industry are needed in order to reach a critical mass that is needed to reach certain agglomeration economies (Braunerhjelm and Feldman  2006). If the build- up of capacity to this level of critical mass is not reached due to the lack of complementary investments, there might be a role to play for governments to overcome coordination failure, for example by providing investment guarantees for entrepreneurs (see Rodrik  2007).Such industrial policy is not about ‘picking winners’ or comprehensive planning, but encouraging experiments with new types of economic activity (Rodrik2007). Since it is impossible to judge winners and losers in advance, competent and growth-oriented entrepreneurs should be encouraged to try, success should be rewarded, and failure should not be coddled (Nelson and Pack  1999). These clusters do not have to be close to the technology frontier (as in advanced capitalist economies). The real policy implications arise from thinking carefully about the particular sources of advantage for a nascent cluster  (p. 2 )  and why that source might yield short-term complements with the potential to become l ong-term substitutes (Bresnahan, Gambardella, and Saxenian  2001). Cooperation of clusters in developing countries with existing richer economies is not ‘colonialist’. Take for example the linkages with the US. India and Taiwan are linked to the US (especially Silicon Valley) via outsourcing of software services and manufacturing (due to low labour costs), but also by a returning group of expatriates who have worked there, and who see the benefits of long distance collaboration (Saxenian  1999).There is a flow of people—the so-called Argonauts (Saxenian  2006)—and ideas back and forth between rich and emerging economies. Migrant workers tend to be among the most entrepreneurial in society. Governments of developing countries should not only look at these expatriate workers as a source of remittances. Given their entrepreneurialism, skills, and exposure to business in the developed world, as well as the desire of many of them to return home, they may be very important as a source of self-discovery in their country of origin (Rodrik  2007).In addition to developing the private sector, these return migrants may provide the new elite needed for building up a civil society. Only a fraction of the money spent on attracting FDI would be needed to target nationals abroad. This would attract more knowledgeable human capital and durable investments than most FDI will do. Once critical mass is reached within a regional cluster, it is likely to generate or attract growth-oriented entrepreneurs (e. g. Argonauts), who in turn stimulate further macroeconomic growth. 4. 5. 3  Limitations and further researchThe regression analyses in this chapter are of limited value: they have not only simplified the range6and (linear) effects of determinants for economic development, they have also dumbed down economic development to economic growth over a short-term (four-year) period. We know that sustaining growth is more difficult (and caused by diff erent factors) than igniting it (Rodrik  2007). This also connects to one of the other shortcomings: sustaining growth probably requires much more extensive institutional reform than can be properly taken into account in linear regression analyses.Next to better measures of institutions, future research should take into account samples with low-income countries and a larger number of medium-income and transition countries, and multiple years in order to achieve more robust empirical analyses. In addition, our data did not allow for testing the multiplicative effect of entrepreneurship, so we only analysed the additive effect. A larger number of cases would enable the inclusion of the more traditional indicators of capital and labour in the analyses, and allow for testing the multiplicative effect.