Monday, August 25, 2008

Quantitative research uses objective measurements and statistical analysis of data

Friday, August 22, 2008

Quantitative research and Qualitative research

Quantitative research involves attaching numbers to relationships between variables (Hopkins, 2000). Quantitative research uses objective measurements and statistical analysis of data that is collected from a well-controlled setting. On the contrary, qualitative research is rooted in phenomenology. Qualitative research involves intensive narrative data collection in order to understand the way things are and to gain insights into how things got to be that way and how people feel about the way things are (Gay & Airasian, 2003). Qualitative data is collected in natural settings and “focuses on understanding social phenomena from the perspective of the human participants in the study” (Ary, Jacobs, & Razavieh, 2002, p. 22). Usually, qualitative research is for generating theory while quantitative research focuses on testing theory (Ary, et al., 2002).

Quantitative research has two types: non-experimental and experimental (Ary et al., 2002). In a non-experimental study, no attempt is made to change behavior or conditions; researchers measure things as they are (Hopkins, 2000). Major forms of non-experimental research are survey research (exploratory studies), correlational studies, and causal-comparative (or ex post facto) studies. Survey research is used to measure the characteristics of different groups or to measure their attitudes and opinions toward some issue; correlational research is done to determine relationships among two or more variables from the same group of people and to examine the strength and direction of relationships among variables (Ary, et al., 2002); causal-comparative research investigates “the cause for or the consequences of differences between groups of people” (Fraenkel & Wallen, 1996, p. 10). It should be noted that causal-comparative research does not establish a causal relationship among the variables, because it does not manipulate the independent variable that has already occurred naturally (Ary et al., 2002).

Monday, June 30, 2008

General considerations-research





Research papers usually have five chapters with well-established sections in each chapter. Readers of the paper will be looking for these chapters and sections so you should not deviate from the standard format unless you are specifically requested to do so by the research sponsor.

Most research studies begin with a written proposal. Again, nearly all proposals follow the same format. In fact, the proposal is identical to the first three chapters of the final paper except that it's writtten in future tense. In the proposal, you might say something like "the researchers will secure the sample from ...", while in the final paper, it would be changed to "the researchers secured the sample from ...". Once again, with the exception of tense, the proposal becomes the first three chapters of the final research paper.

The most commonly used style for writing research reports is called "APA" and the rules are described in the Publication Manual of the American Psychological Association. Any library or bookstore will have it readily available. The style guide contains hundreds of rules for grammar, layout, and syntax. This paper will cover the most important ones.

Avoid the use of first person pronouns. Refer to yourself or the research team in third person. Instead of saying "I will ..." or "We will ...", say something like "The researcher will ..." or "The research team will ...".

A suggestion: Never present a draft (rough) copy of your proposal, thesis, dissertation, or research paper...even if asked. A paper that looks like a draft, will interpreted as such, and you can expect extensive and liberal modifications. Take the time to put your paper in perfect APA format before showing it to anyone else. The payoff will be great since it will then be perceived as a final paper, and there will be far fewer changes.

Wednesday, April 30, 2008

Employee Survey
Survey Design Tips
Sibin Mohan’s Research Statement

Friday, April 4, 2008

Tips For Developing An Effective Questionnaire

by: Nick Hill

Developing the questionnaire is undoubtedly the most important part of conducting a survey. The quality of the questions will determine the quality of the results and the effectiveness of your survey. Here are 12 tips for developing an effective questionnaire.

1. Write a good introduction - The beginning of your survey should have an introduction of the survey. It should state your objective in a way that grabs the attention of potential respondents and encourages them to take the survey. Also, since it is easy for online survey respondents to abandon your survey, you should include instructions on how to complete the survey and an estimate of how much time it will take.

2. Ask questions that provide the information you need - Always keep your objective and the information that you need to gather to achieve it in mind while asking the questions. Also, it is best to avoid the temptation to gather "extra" bits of information that are "nice to know" but irrelevant to your objective.

3. Ask important questions first, demographic questions last - Since it is very easy for online survey respondents to abandon your survey, always ask the important questions first and the demograhic questions last.

4. Organize the questions in logical groups - Always organize the questions in logical groups. It makes it easier for your respondents to understand and answer the questions, thus increasing the quality of the results.

5. Use plain, easy to understand language - The most effective surveys always use plain, easy to understand language. Using unclear or ambiguous language will give you misleading results. So test your survey thoroughly to ensure that it is indeed easy to understand.

6. Avoid technical terms, jargon, and acronyms - If you use technical terms, jargon, and acronyms, your respondents might not understand them, get frustrated, and abandon your survey. So strictly avoid them.

7. Use even number of responses - Whenever possible, use even number of responses for multiple choice questions. That way the respondents have to give a positive or a negative opinion, they can't give a "neutral" answer.

8. Randomize the responses - Whenever it makes sense, randomize the order in which responses are displayed. This removes "order bias" from the responses.

9. Avoid unnecessary graphics and embedded components - Although it might be tempting to use graphics and embedded components, their use increases the time it takes to download and display your survey. So use them only when it is absolutely necessary and certainly don't overdo it.

10. Be sensitive to the feelings of your respondents - Always be sensitive to the feelings of your respondents. If you offend them, they might abandon your survey. So test your survey to ensure that it is not offending to any group of people.

11. Thank the respondents - Your respondents spend the time to take your survey. So never forget to thank them for completing the survey.

12. Keep it short - As a general rule, keep your survey short, simple, and to the point.


© Web Based Survey Software (http://www.web-based-survey-software.org) 2004

Monday, March 31, 2008

Cool Tips for Thesis Writing

A thesis is a research report similar to essays and term papers, but it goes into much more detail. A thesis is usually a scientific report. A thesis is a great way for them to see how well a student can do. Many instructors consider a thesis a major part of the student’s grade. Learning how to write a thesis is important especially if the student is considering graduate school. Graduate schools usually require a PhD thesis.

The first part of writing a thesis should begin with the outline including chapter headings, sub-headings, and charts/graphs. Let this outline be a guide to writing the thesis. Once it is broken down into different headings and sub-headings it will not seem such a massive job. The outline also helps in organization. A word to the wise is to have the outline and all work on the thesis to be on back-up files. If for some reason the original disk malfunctioned, all of the work would not be lost.

Set goals and deadlines. Use the outline to set these goals and deadlines. Reward yourself when you accomplish these goals. The sections of a thesis are:

- Title page (This includes the author’s name, title, and name of university

- Abstract (A concise summary of the research topic. This should include methods and final results of the research paper)

- Table of Contents

- Introduction (This includes why the topic is important and why you have chosen the topic. State the problem in simple terms. It should include background information about the topic. Never overestimate the reader’s familiarity with the topic. Define any terms necessary. This section should be written several times because it is one of the most important parts of the thesis. It needs to be interesting enough to catch the reader’s attention and keep them reading)

- Literature Review (This should include an annotated bibliography of sources showing what research has been done on the topic)

- Methods (What are your methods of research? Do you plan on questionnaires? Observation? What is your specific method of determining whether your thesis is correct?)

- Results and discussion (This discusses what you found during your research process. Different graphs and charts should be used to display the results you found. Carefully describe the conditions that led to the results of your research)

- References (Be sure to cite every source used in proper style such as APA or MLA)

- Appendices (This should include any materials that you consider important but not in the actual thesis)

Different instructors may have different parts of a dissertation or PhD thesis. These were examples of the common subtopics in a thesis. If in doubt about any section, do not be afraid to ask your professor questions. Different instructors may put more emphasis on different sections so knowing for sure what the professor wants is important.

Set goals for each section of the thesis so it does not seem so overwhelming. Once you complete each section, proofread it. Remember to make back-ups of each of these sections. Do at least three rewrites of each section. It is easier to correct mistakes one section at a time than trying to correct mistakes as a complete thesis. Have someone proofread each section. Check for spelling, punctuation, and grammar mistakes. Revisions are an important part of any writing assignments, but it is especially important to correct any errors in a thesis. Take pride in your work because it may be something that you will show future employers.

About The Author
Tamara Johns is a staff academic essay and term paper writer and researcher at CustomPapers.com. For more details check article about Dissertation Mistakes , Dissertation Proposals, and Writing a Dissertation Abstract.

Friday, March 28, 2008

Thesis Essay Writing Guidelines Every Student Ought to Know

by: Linda Correli

Writing a thesis essay is one of the challenges that students face in their academic life. The main reason why so many students dread writing a thesis essay is its baffling complexity, which is hard to handle at times.

However, writing a thesis essay can be much easier, if you already know how it should be written. And the secret formula of writing a high quality thesis essay is incredibly simple: all you need is to understand the initial purpose of thesis essays and follow the tips for thesis essay structure that you’ll find below.

1. Thesis Essay Peculiarity

Thesis essay is an essay elaborating on the original research and arguing a specific point of view. It requires an argumentative topic on which you have a strong opinion and want to prove it by means of research findings and information analysis. To put it in other way, thesis essay is a scientifically-minded piece of writing.

Consequently, a thesis essay is much more demanding than the rest of essays. It demands responsibility, analytical skills, ability to summarise, compare, and contrast. In order to write a high-quality thesis essay you need to be persuasive and able to prove your case no matter what.

2. Thesis Essay Topic

Thesis essay topic requires tender treatment. To choose the one that is your best bet, stick to the following:

1. the topic must be to your liking, that is you must have strong feelings on its account and hold a solid point of view as far as the solution of this problem goes;
2. your thesis essay topic must be argumentative, ambivalent and thought-provoking;
3. your thesis essay topic should not be widely researched and be on everybody’s lips. On the contrary, it must be a problem that is not known to the public at large and still is concerns us very much.

Get down to choosing a thesis essay topic with these tips in mind, and you will find one truly argumentative and interesting.

3. Thesis Essay Structure

Thesis essay structure must be carefully thought over, since it is the foundation on which you build your proposition and prove your rightness. With a proper thesis essay structure you will create the necessary impression on the readers and make them reject their own views and stick to your point.

Your thesis essay structure should be like this:

1. the introduction must include a statement of your hypothesis, which is a summary of your controversy;

2. confirmation of your hypothesis must be logically arranged:

a. first, provide a short digression in the history of the problem corroborating it by the past attempts at its solution;
b. analyze the problem at the present;
c. prove your hypothesis by the supporting evidence you came across when researching the thesis essay topic;
d. compare your hypothesis with other existing propositions and prove why yours is the best solution;

3. reinforce your thesis statement at the end of the essay by providing a persuasive summary of your thesis essay to make the readers come over to your side once and for all.

This is the proven way of organising thesis essays. So, do not hesitate to use this structure in your paper.

4. The Use of Supporting Evidence

As it has been previously mentioned, your hypothesis in a thesis essay needs a back up in the form of supporting evidence from reliable and relevant sources. The related sources you can use to strengthen your proposition can be:

1. past research and writings and their impact on the study;
2. facts, statistics, and the testimony of others through personal interviews and questionnaires;
3. or articles and books;
4. and examples.

You do not have to conduct a deep research for your thesis essay, as you do for a research paper. All you need is to explore your topic deep enough to have a sufficient amount of evidence and proofs. However, make sure that the information you plan to use is up-to-date and is taken from reliable sources. Otherwise, it will be easy to discredit your proposition.

5. Disprove the Opposing Arguments

Every hypothesis has a weak point, which, if wisely used by opponents, can destroy it all together. To avoid it, try to identify weak points of your proposition and the possible ways how they can be used by your opponents. Then find counterarguments that will rebut your antagonist’s sharp rejoinders. Try to anticipate any objections the readers may have and rebut them at once.

That is all you need to know in order to write a good thesis essay. Be sure that with the above tips in mind you will easily master thesis essay writing and even come to like finding controversial topics and forming your hypothesis on its account. Thesis essay writing will no longer be a tedious burden for you.


About The Author

Linda Correli is a staff writer for http://www.go2essay.com/ She specializes in writing History, Literature and English essays and book reports, as well as admission essays, personal statements and letters of recommendation.

Thursday, March 27, 2008

How To Make Thesis Statement

by: Charles Andrew

The main idea behind a thesis statement is to give a glimpse of the thesis. In other case if the writer is trying to prove his point or is trying to put forward his idea then a thesis statement can be described as a statement that is put forward as a premise to be proved or maintained. It is generally very short in length, usually comprising of two or three sentences. As the thesis statement gives the reader, a brief idea of the thesis therefore it is recommended that it should be used in the introductory paragraph. However in some rare cases the writers tend to use it in the concluding paragraph. As we all know that “First impression is the last one”. Similarly a good thesis statement leads to a good thesis or in other words a good thesis statement guarantees an impressive and outstanding upcoming thesis. Thus the thesis statement is an integral part of thesis and utmost care should be taken while writing an appropriate one. A thesis statement can be a quote that could create a clear picture of the thesis or its concept. If the writer is trying to prove his point then it can be a problem statement. The problem statement gives the reader a hint of what will be the thesis all about.

You need not to be petrified or worried if your educator asks you to write a thesis statement for your assignment as http://www.thesisspecialist.com lends you a hand in composing the appropriate statement for your thesis possessing a comprehensible approach and prepared by a pedagogic person.

Making an attention-grabbing thesis statement is the most difficult task to achieve while writing your paper and it acts as the basis for your entire assignment. For a methodical and systematic thesis, an accurate thesis statement is of utmost significance. A thesis statement is the prĂ©cis of the subject matter explained in the document and facts laid down in it. A first-class thesis statement should be capable of capturing the reader’s mind, offering him a concise overview of the proposal or an argument being discussed at a first look.

There are various ways for putting the thesis statement in writing. We provide help in generating a one-of-its-kind thesis avowal varying from an analytical to argumentative ones.

Charles Andrew

Tuesday, March 25, 2008

The important things of research

1. There are 20 questions of multiple choice (Part A=40%)
2. 20 of true/false questions (Part B=40%)
3. Two of structure questions (Part C=20%)

-Types of research (basic and applied research)
-Induction and deduction
-Literitur review
-Research design-tpes of research design, time horizon
-Research Proposal
-The meaning of qualitative and quantitative research
-Research Process
-Research topic
-Research question
-Symptoms
-Theoritical framework
-Conceptualization
-Types of variables
-Hipotesis
-Types of Sampling- process and also the advantages and disadvantages
-Sampel and population
-Scientific research

Sampling Method
Stratified sampling
In statistics, stratified sampling is a method of sampling from a population.

When sub-populations vary considerably, it is advantageous to sample each subpopulation (stratum) independently. Stratification is the process of grouping members of the population into relatively homogeneous subgroups before sampling. The strata should be mutually exclusive: every element in the population must be assigned to only one stratum. The strata should also be collectively exhaustive: no population element can be excluded. Then random or systematic sampling is applied within each stratum. This often improves the representativeness of the sample by reducing sampling error. It can produce a weighted mean that has less variability than the arithmetic mean of a simple random sample of the population.

Stratified sampling strategies
1. Proportionate (berkadar)allocation uses a sampling fraction in each of the strata that is proportional to that of the total population. If the population consists of 60% in the male stratum and 40% in the female stratum, then the relative size of the two samples (three males, two females) should reflect this proportion.
2. Optimum allocation (or Disproportionate allocation/(tidak berkadar)) - Each stratum is proportionate to the standard deviation of the distribution of the variable. Larger samples are taken in the strata with the greatest variability to generate the least possible sampling variance.

Practical example
In general the size of the sample in each stratum is taken in proportion to the size of the stratum. This is called proportional allocation. Suppose that in a company there are the following staff:



Systematic sampling

Systematic sampling is a statistical method involving the selection of every kth element from a sampling frame, where k, the sampling interval, is calculated as:

k = population size (N) / sample size (n)
Using this procedure each element in the population has a known and equal probability of selection. This makes systematic sampling functionally similar to simple random sampling. It is however, much more efficient (if variance within systematic sample is more than variance of population) and much less expensive to carry out.

The researcher must ensure that the chosen sampling interval does not hide a pattern. Any pattern would threaten randomness. A random starting point must also be selected.

Systematic sampling is to be applied only if the given population is logically homogeneous, because systematic sample units are uniformly distributed over the population.

Example: Suppose a supermarket wants to study buying habits of their customers, then using systematic sampling they can choose every 10th or 15th customer entering the supermarket and conduct the study on this sample.

This is random sampling with a system. From the sampling frame, a starting point is chosen at random, and choices thereafter are at regular intervals. For example, suppose you want to sample 8 houses from a street of 120 houses. 120/8=15, so every 15th house is chosen after a random starting point between 1 and 15. If the random starting point is 11, then the houses selected are 11, 26, 41, 56, 71, 86, 101, and 116.

If, as more frequently, the population is not evenly divisible (suppose you want to sample 8 houses out of 125, where 125/8=15.625), should you take every 15th house or every 16th house? If you take every 16th house, 8*16=128, so there is a risk that the last house chosen does not exist. On the other hand, if you take every 15th house, 8*15=120, so the last five houses will never be selected. The random starting point should instead be selected as a noninteger between 0 and 15.625 (inclusive on one endpoint only) to ensure that every house has equal chance of being selected; the interval should now be nonintegral (15.625); and each noninteger selected should be rounded up to the next integer. If the random starting point is 3.3, then the houses selected are 4, 19, 35, 51, 66, 82, 98, and 113, where there are 3 cyclic intervals of 15 and 5 intervals of 16.


systematic sampling - every nth member of the population is sampled. The list being sampled may be ordered (alphabetical, seniority, street number, etc).
Question : Is it equivalent to simple random sampling? Strictly speaking the answer is No!, unless the list itself is in random order, which it never is (alphabetical, seniority, street number, etc).

Advantages

1. easier to draw, without mistakes (cards in file)
2. more precise than simple random sampling as more evenly spread over population

Disadvantages

1. if list has periodic arrangement then sample collected may not be an accurate representation of the entire population.

Saturday, March 22, 2008

Thesis/Dissertation Simplified – Learn how Dissertation and Thesis are Different

How can you write your Thesis/Dissertation when you don’t know the difference between a dissertation and thesis? How can you write your thesis/dissertation if you don’t know the difference between a thesis/dissertation and thesis statement? How can you write your thesis/dissertation if you don’t know the difference between a Master’s and PhD thesis/dissertation?

The answer to all these questions is, “You can’t write your thesis/dissertation, PERIOD”. It is because you simply can’t write when you don’t know what to write. Let’s now learn how they differ from each other:

Dissertation and Thesis – How do they differ?
The difference between a dissertation and thesis is fairly simple:

If you are in the US: You write a dissertation if you are doing your PhD and you write a thesis if you are in Master’s program.

If you are in the UK: You write a thesis if you are doing your PhD and you write a dissertation if you are in Master’s program.

Thesis/Dissertation and Thesis Statement – How do they differ?
As we now know how dissertation and thesis differ, we now need to understand what a thesis statement is in order to know the difference between a thesis/dissertation and thesis statement.

A thesis statement defines your main argument. It shows what you believe, what you want you readers to know and what you want to prove. It basically states your point of view and summarizes your argument you will make in your paper. It is usually stated in one sentence after a brief introduction.

Master’s and PhD Thesis/Dissertation – How do they differ?
Master’s Thesis/Dissertation: You do a thorough research on a particular topic and present your discourse depending on what type of information you have collected on the subject with your views on it.

PhD Thesis/Dissertation: It requires your original research and adds something new to the existing literature. It usually takes many years to complete it.
So, you have now understood the difference between a dissertation and thesis, thesis/dissertation and thesis statement & Master’s and PhD thesis/dissertation. The words Dissertation and thesis are, however, often used interchangeably so make sure you know what you have to write.

How to get your dissertation paper published?

After completing a dissertation paper, most students want to know how to get it published. First of all, you should own the copyright. So bind your dissertation paper and then fill out the copyright form. If you live in the UK then submit the form and the required number of bound copies to The British Library. If you live in the US then submit the form and the required number of bound copies to The Library of Congress.

When you are ready to get your dissertation paper published, talk to your advisor and seek his advice. It will be difficult to publish your non-fiction dissertation paper work without previous experience of publication. Your advisor will not only guide you but will also help you revise your dissertation paper according to the requirements of the publisher.

You have three options to choose from in order to get your dissertation paper published:

1) Publish Your Dissertation Paper in a Journal:
Find a suitable journal for your dissertation paper. In order to find one, go through their guidelines and find out their requirements and what kind of content they are looking for. Check if you can publish your complete dissertation paper or only some part of it. Also find out what their submission guidelines are. For example, if they are looking for content related to your filed of study or not, or if they only want experienced authors whose works have previously been published, etc. After going through the details submit your work and wait for their reply. They will review your work and inform you. If it’s not accepted, go for another journal.

2) Publish Your Dissertation Paper as a Book:
Find a publisher who specializes in publishing dissertation papers in your field of study. Make your dissertation paper look like a book. It will require thorough revision and editing if you are getting your dissertation paper published for general public. I advise you to consult with academic publishers as well. You will first have to submit a book proposal to a publisher. Your book proposal will explain what sort of material you want to publish. Make sure you don’t submit your complete manuscript unless they are interested.

3) Self-Publishing:
If you only need to have some bound copies of your dissertation paper that you can share with others then you may use something like Lulu.com.
So, when you are ready to get your dissertation paper published, choose the option that best suits your needs. Talk to your advisor about it as well as they will unquestionably guide you in the right direction.

3 Sure-Fire Ways to Select a Masters Dissertation Topic

Are you ready to come up with an interesting Masters Dissertation topic that not only will you find interesting but which will also keep you focused? If so, then I am about to discuss with you that how you can select a masters dissertation topic. But before we do that, I must tell you if you are currently taking graduate courses then this is the best time to select a topic as it will be easier to come up with a possible topic.

1. Organize Your Masters Dissertation Topic Research:
Keep track of your masters dissertation research and keep it organized. This way you won’t have to look for the same matter again and it will prevent you from wasting your time. The more organized your dissertation topic research is, the earlier you will be able to select a topic. Don’t make the process painful by looking for the same matter or files again

2. Find an Interesting Masters Dissertation Topic:
If your masters dissertation topic is not interesting, the chances are you will end up procrastinating. You might even end up giving up your dissertation and degree. Write down when you find something interesting. Always take notes when you listen to lectures as you might find an interesting idea for your masters dissertation topic. Therefore, keep a notebook with you and write down whenever you find something interesting, that you think could possibly be used as a topic.

3. Make Sure Your Masters Dissertation Topic is Original:
In order to come up with something original you need to know what has been found and studied before and then identify the gaps in knowledge in your field. Once you know how these gaps can be filled, you will be able to come up with a topic.

So, now you can come up with a masters dissertation topic. Your dissertation doesn’t only require research; your dissertation topic requires in-depth research as well. Get ready to do an in-depth research, select a topic, complete your dissertation and earn your degree.

Master’s and PhD Thesis/Dissertation – How do they differ?

Master’s Thesis/Dissertation: You do a thorough research on a particular topic and present your discourse depending on what type of information you have collected on the subject with your views on it.

PhD Thesis/Dissertation: It requires your original research and adds something new to the existing literature. It usually takes many years to complete it.
So, you have now understood the difference between a dissertation and thesis, thesis/dissertation and thesis statement & Master’s and PhD thesis/dissertation. The words Dissertation and thesis are, however, often used interchangeably so make sure you know what you have to write.

Thursday, March 20, 2008

Typical Viva Questions

Here are some generic viva-questions - you should instantiate each question for your particular thesis, and have a framework for answering it worked out before the viva.

I have tried to cluster related questions together here - they are not necessarily in order of importance, nor in the order that they are likely to be asked at the viva.

General Questions
What is the area in which you wish to be examined? (particularly difficult and important if your thesis fits into several areas, or has several aspects, or seems to fit into an area of its own as mine does).

In one sentence, what is your thesis? (Resist the temptation to run from the room!)

What have you done that merits a PhD?

Summarise your key findings.

What are you most proud of, and why? This may be asked (again) towards the end of the viva.

What's original about your work? Where is the novelty? Don't leave it to the examiners to make up their own minds - they may get it wrong!

What are the contributions (to knowledge) of your thesis?

Which topics overlap with your area?
For topic X:
How does your work relate to X?
What do you know about the history of X?
What is the current state of the art in X? (capabilities and limitations of existing systems)
What techniques are commonly used?
Where do current technologies fail such that you (could) make a contribution?
How does/could your work enhance the state of the art in X?
Who are the main `players' in X? (Hint: you should cluster together papers written by the same people)
Who are your closest competitors?
What do you do better than them? What do you do worse?
Which are the three most important papers in X?
What are the recent major developments in X?
How do you expect X to progress over the next five years? How long-term is your contribution, given the anticipated future developments in X?


What did you do for your MPhil, and how does your PhD extend it? Did you make any changes to the system you implemented for your MPhil?

What are the strongest/weakest parts of your work?

Where did you go wrong?
Why have you done it this way? You need to justify your approach - don't assume the examiners share your views.

What are the alternatives to your approach?
What do you gain by your approach?
What would you gain by approach X?

Why didn't you do it this way (the way everyone else does it)? This requires having done extensive reading. Be honest if you never thought of the alternative they're suggesting, or if you just didn't get around to it. If you try to bluff your way out, they'll trap you in your own words.

Looking back, what might you have done differently? This requires a thoughtful answer, whilst defending what you did at the time.

How do scientists/philosophers carry out experiments?

How have you evaluated your work?
intrinsic evaluation: how have you demonstrated that it works, and how well it performs?
extrinsic evaluation: how have you demonstrated its usefulness for a specific application context?


What do your results mean?

How would your system cope with bigger examples? Does it scale up? This is especially important if you have only run your system on `toy' examples, and they think it has `learned its test-data'.

How do you know that your algorithm/rules are correct?

How could you improve your work?

What are the motivations for your research? Why is the problem you have tackled worth tackling?

What is the relevance of your contributions?
to other researchers?
to industry?


What is the implication of your work in your area? What does it change?

How do/would you cope with known problems in your field? (e.g. combinatorial explosion)

Have you solved the field's problem that you claim to have solved? For example, if something is too slow, and you can make it go faster - how much increase in speed is needed for the applications you claim to support?

Is your field going in the right direction? For example, if everyone's been concentrating on speed, but the real issue is space (if the issue is time, you can just wait it out (unless it's combinatorially explosive), but if the issue is space, the system could fall over). This is kind of justifying why you have gone into the field you're working in.

Who are your envisioned users? What use would your work be in situation X?

How do your contributions generalise?
To what extent would they generalise to systems other than the one you've worked on?
Under what circumstances would your approach be useable? (Again, does it scale up?)

Where will you publish your work? Think about which journals and conferences your research would best suit. Just as popular musicians promote their latest albums by releasing singles and going on tour, you should promote your thesis by publishing papers in journals and presenting them at conferences. This takes your work to a much wider audience; this is how academics establish themselves.

Which aspects of your thesis could be published?

What have you learned from the process of doing your PhD? Remember that the aim of the PhD process is to train you to be a fully professional researcher - passing your PhD means that you know the state of the art in your area and the directions in which it could be extended, and that you have proved you are capable of making such extensions.

Where did your research-project come from? How did your research-questions emerge? You can't just say "my supervisor told me to do it" - if this is the case, you need to talk it over with your supervisor before the viva. Think out a succinct answer (2 to 5 minutes).

Has your view of your research topic changed during the course of the research?

You discuss future work in your conclusion chapter. How long would it take to implement X, and what are the likely problems you envisage? Do not underestimate the time and the difficulties - you might be talking about your own resubmission-order! ;-)

Particular Questions
Most of the viva will probably consist of questions about specific sections of your thesis, and the examiner should give a page-reference for each question. According to Alex Gray, these questions fall into six categories:

Clarification. The examiners ask you to explain a particular statement in the thesis. In some cases, their lack of understanding may be due to a typo, e.g. "Why did you connect the client to the sewer?" Also, "not" is a small word which makes a big difference! ;-)
Justification.
Alternatives considered. Be honest if you didn't consider alternatives, otherwise you'll be digging a hole for yourself.
Awareness of other work.
Distinction from similar work. Especially recent publications where others are working in the same area - what are the similarities and differences between your work and theirs?
Correction of errors (typos, technical errors, misleading statements, and so on).

Acknowledgements
Much of the material on this page comes from my supervisor Nick Filer, from CS700/CS710, from questions I've been asked at the end of various presentations I've given, and from my own viva (most of the questions there were thesis-specific). I added questions from the external websites given at the end of this document. I also updated this document in the light of Alex Gray's keynote speech, "Surviving the PhD Viva: An External Examiners Perspective" at the 2002 Research Students' Symposium.

If you can think of any viva-style questions that are not covered by the above, please do not hesitate to tell me, and I will consider them for inclusion on this page.

Finally, I found my own viva much less stressful than I thought it was going to be. The examiners know that it's an ordeal for anybody, so they should go out of their way to put you at your ease and make you feel comfortable. I was amazed how calm I was, even when I went back to hear the result. If you're worried about getting an `impossible' resubmission-order, remember it's not the examiners' job to set insurmountable hurdles - they want you to pass as soon as possible.

The Viva itself

The PhD viva is an open-book exam: you can bring any materials you want. Here is what I think one should bring to the viva:

a copy of your thesis, obviously - you can stick yellow `post-it' notes on it (e.g. anticipated questions and answers), although I personally abhorred the idea of preparing from my thesis itself;
your list of anticipated viva questions and your answers;
printouts of the results of any post-submission experiments;
the chapter-summaries you made for revision;
all the notebooks you should have been keeping since the start of your research (the notebooks need to be indexed so that you can look things up);
any papers such that when you reviewed them in the thesis, you regurgitated something they said blindly without really understanding it (in my case, I identified two such papers, but I brought a dozen potentially contentious papers to the viva);
printouts of any files or emails containing useful ideas which you haven't documented elsewhere;
tissues, paracetemol, &c. in case of any unexpected bouts of sneezing, headaches, &c.

At my viva, I gave a presentation (using slides) about some experiments I did after I submitted my thesis. But it's unusual for the candidate to give a presentation, and your supervisor should advise you if it is appropriate to do this. If you do give a presentation, be prepared to be flexible - I was asked to speed up and just give the highlights.

It is not the norm, in this department (I do not speak for other departments/universities), to be expected to give a practical demonstration of your work at the viva, but you could always offer to do so if you think it will help your cause (unlikely).

Anyone can attend a PhD viva, but only the examiners and the candidate can participate. (This means it may be a good idea to attend someone else's viva before your own, though I've never had the balls to gate-crash a viva! :-o )

Your supervisor should definitely attend your viva, although (s)he is usually not allowed to participate unless invited to do so by the examiners. It might be an idea to keep an eye on the body-language of your supervisor to see if you're going wrong! ;-)

A viva typically lasts two hours (but as long as it takes - mine lasted 2h22m), and a common approach is for the examiners to go through the thesis sequentially, asking questions.

Just because they ask a lot of questions doesn't mean you're going to fail. They don't give away the result before or during the viva, but you may be asked to wait around for the result at the end (about half an hour), so that they can explain the result to you - particularly if you have to resubmit your thesis (failure without the option of resubmission is very rare, and is not going to happen if you submit anything resembling a sensible thesis).

Tips:

Relax and enjoy it, if possible!
Ideas should flow out from you without a lot of prompting.
Listen carefully to the questions and take your time answering them.
Answer your questions succinctly (a rough guideline is 2 to 3 minutes each - no 20-minute diatribes!). Avoid going off at a tangent.
Try to make your answers initially inclusive (spot overlaps), analytical, and then if appropriate dismissive or point out the limitations - and the effects of these limits.
Generic viva questions, such as the ones given in the section below, require imagination to answer well!
Answers may utilise a wide variety of examples and domains. They are a test of your breadth of knowledge as well as depth of knowledge which is expected of a PhD student.
Handling difficult questions:
If you don't understand the question, ask for clarification. Paraphrase the question in your own words and say, "is this what you mean?" State your assumptions.
Treat vague questions as invitations to tell the examiners that you know your area and how it fits into related areas. Try to link the question to the questions you have anticipated and their stock answers. After writing a thesis, you should have one big, connected network of discussion in your head, so you need to jump in at the appropriate place for a given question.
If they have a misconception about your work, try to pin it down and explain it.
If you think the question is irrelevant, explain why you think it is irrelevant (it may be that you need to be more broad-minded).
If you really can't answer a question:
Be honest.
If you have any idea at all, say it.
Say, "I can't answer this on the spot, but I should be able to work it out in my own time."
If it's about literature you haven't come across, thank the questionner and ask for a reference.

Preparing for the Viva: After you submit

The most important goal in preparing for the viva is to keep the subject alive in your head.

Try to anticipate the questions you'll be asked in your viva and keep working on a file of anticipated questions (both the generic questions listed on this web-page, and questions specific to particular sections of your thesis) and your answers. If you said anything without understanding it 100%, or anything you have doubts about having justified properly, add it to your viva file.

You can go into university after you've submitted your thesis and your registration has expired - doing some more practical work may (or may not) help to keep the subject alive in your head (you could do experiments and take printouts of the results to the viva).

However, the main preparation for the viva is reading. These are the things to prioritise:

Know your thesis inside-out. Compile a thesis summary (see above) if you didn't do so before you submitted - revising from that rather than from the thesis itself will help you focus on the strategic level (a half-line summary of each paragraph in the thesis should suffice to remind you of every important point in the thesis). You should read your thesis summary in a continuous cycle while you're waiting for the viva, and you should read the thesis itself at least once after you submit it and before the viva. Try to read it from the perspective of the examiners.
If your thesis contains mathematical formulae, check them carefully so that you're confident, by the time of the viva, that they're correct. If they're not correct, work it out in advance so that you're not flustered by mathematical mistakes at the viva.
Be familiar with the references cited in your thesis, because that's the literature your examiners are most likely to ask you about. Read anything you have cited without reading (not that you should cite things without reading in the first place!).
The examiners could also ask you about literature not in the thesis, to test whether you are widely-read in your area.
So make sure you're familiar with the literature - not everything you've read in the last three years, but the more important stuff.
Look for recent review/survey papers of related areas. You need to be able to discuss the state of the art in any area related to your thesis.
Recent publications tend to be particularly important (what are the recent developments in your field?), although they can't ask you about anything published after you submitted your thesis.
Read the examiners' publications to get a feel for where they're coming from, what things they consider important, and which topics they consider relevant.
Don't stop reading until after the viva.

It might be an idea to publish a paper or two between submitting your thesis and the viva - I wish I had done so. Try to write papers from different perspectives.

The time between submitting the thesis and the viva varies greatly. I submitted my thesis on 28th September 2001, and had my viva on 18th September 2002! My thesis was very long (390 pages including appendices), and there was a delay in finding a suitable external examiner, but above all you have to remember that your examiners will be busy with other things too!

The shortest time I've heard of between submission and viva is three weeks (different subject, different university).

They have to give you at least two weeks' notice before the viva. I got five weeks' notice. My internal examiner suggested a couple of dates, I chose 18th September and asked for 14:00 in IT406, and this was officially confirmed a few days later.

Preparing for the Viva: Before you submit

It's crucial to get the philosophy of your thesis (as set out in your Chapter 1) absolutely correct, and clear in your mind by the time of the viva, because if the examiners find holes, they'll run rings round you.

They could ask you to explain/justify any statement in the thesis, so beware of baring nasty branches for clarification at the viva! Identify the contentious statements in the thesis, which you anticipate having to defend in the viva. A good supervisor will point out the contentious statements and grill you over them. Start a file of anticipated viva questions.

The conclusion chapter is a major one to focus on in anticipating viva questions - especially where you criticise your work!

Obviously, it's essential to know your own thesis thoroughly. I think it's a great idea to compile a brief summary of each section before you submit - enough to remind you of what's in each section, paragraph by paragraph or similar (my thesis summary is very different to, and shorter than, my thesis plan, where I basically wrote down all the points I could think of, then when I wrote it up, I added and deleted points, and changed the structure). Compiling a thesis summary before you submit has the advantages that you may spot strategic-level flaws in time to fix them, and will enable you to revise for the viva from the thesis summary rather than from the thesis itself.

Don't try to get the thesis perfect and free of minor corrections at the expense of delaying submission. It's almost certain that the examiners will find something to correct, anyway.

Nasty PhD Viva Questions

Dr. Andrew Broad

A PhD candidate needs to anticipate the questions that are likely to be asked in the viva - the "horrible ordeal where you have to defend your thesis in person before they rip you to shreds." Actually, it's not nearly as bad as it sounds, provided that you enter it having prepared to your utmost.

There are three reasons why PhD candidates have to have a viva: it is so the examiners can see:


whether it is your own work;
whether you understand what you did;
whether it is worth a PhD (i.e. is a contribution to knowledge).

These are the points being examined (according to Alex Gray from the University of Cardiff):


Understanding: that you're ready to become an independent researcher.
Relationship to other work: that you have a command of your subject-area. Similarity to the work of others doesn't detract from novelty!
Novelty - is your work publishable? If you have already published a couple of papers, that should be proof of sufficient originality. Don't panic about recent publications that are very similar to your work - the important thing is to be aware of them, and to know the differences between your work and theirs.
What you have achieved, and that you are aware of its implications. What will it make a difference to?

Demonstration of hypothesis (what you set out to achieve). How have you evaluated/tested your hypothesis? Always be prepared to reconsider your hypothesis if you end up demonstrating something else - it's vitally important that your results match your hypothesis, and that you have a convincing argument for this.
Why did you do it the way you did? Not just your practical work, but everything. For example, your literature review should be focused towards your hypothesis.

Empirical investigation of Intrapreneurial Strategy within Manufacturing sectors in Melaka Malaysia

Al-Mansor Abu Said

Abstract
The primary purpose of this study was to explore a model that examines the relationships among the external environment, intrapreneurial strategy, organizational structure and firms’ performance of manufacturing sectors from the perspective of employees. The model indicated that employees of manufacturing firms’ perceive that their firms’ intrapreneurial strategy makes a highly positive contribution to firms’ performance. The external environment is perceived to have a negative impact on firm’s structures. There is negative linear relationship and negative correlation between Mechanistic-organic structure and Intrapreneurial Strategy. Employees also perceived that there is positive linear relationship and positive correlation between internal organizational characteristics and intrapreneurial strategy. The results are consistent with the expectation that the internal organizational characteristics will increase the implementation of Intrapreneurial Strategy.

The basic value of understanding intrepreneurial strategy is the prediction of certain firm outcomes. Intrapreneurial strategy proved to have a very significant impact on the firm’s performance from the perspective of employees. However, firms’ intrapreneurial strategy was not always perceived to guarantee firm performance success because of the negative impact of the external environment in the manufacturing industry on firm organizational structure. Furthermore, manufacturing firm employees perceived the firm’s structure in the industry was unlikely to contribute to the firm’s intrapreneurial strategy.

The result revealed that a high level of firms’ intrapreneurial strategy is perceived to correlate with a high level of their mechanistic-organic structure from the managers’ perceptions, as hypothesized. In other words, a high level of firms’ entrepreneurial strategy is perceived to correlate with their organic structure from the managers’ perceptions. This indicates that employees tend to perceive that high levels of free-flowing relationship, authority, and communication in the manufacturing firm system correlate with a high level of firms’ intrapreneurial strategy. Thus, it is expected for firms to make sure employees are highly motivated to stay involved throughout their intrapreneurial decision-making process.

Consistently from the hypotheses, firms’ external environment was perceived as a positive predictor of their intrapreneurial strategy. But, external environment was perceived as a negative predictor of mechanistic-organic structure firms’. In other words, employees perceive that high levels of firm’ external environmental change will impact their high levels of intrapreneurial strategy but do not impact the firms’ mechanistic-organic structure.

Also consistently from the hypotheses, firms’ internal organizational characteristic was perceived as a positive predictor of their intrapreneurial strategy. In other words, employees perceive that high levels of firm’ internal organizational characteristic for instant the management support change will impact their high levels of intrapreneurial strategy. However, managers acknowledge that high levels of firms’ intrapreneurial strategy impacted by organic structure can reap high levels of profitability with facets of negative impacts from the external environment in the manufacturing industry.

A LONGITUDINAL STUDY OF THE CAUSES OF TECHNOLOGY ADOPTION AND ITS EFFECT UPON NEW VENTURE GROWTH

J. Robert Baum, University of Maryland

ABSTRACT
This six-year study of the causes of technology adoption and its effect upon new venture growth explains anomalous past findings that new non-technology based ventures have been slow to adopt technology compared with established businesses. In contrast, I found that new ventures invest early in product design technology and low cost marketing technologies; however, they hold off adoption of production and management information technologies. Thus, timing of adoption depends upon technology type. Similarly, the causes of adoption depend upon technology type. Adoption of all technologies were motivated by technology strategy and competitive threat; however, expected cost savings, customer attraction, and financial resources had varying effects. Adoption of all types of technology caused new venture growth.


INTRODUCTION
Adoption of new product/process technology contributes to business success (King, 1994; Utterback, 1994; Williamson, 1985). Indeed, current dominance of the U.S. economy in world markets is ascribed to applied technology benefits for product design, manufacturing process, and management information systems (Council on Competitiveness, 1991). However, new non-technology-based ventures have low rates of technology adoption, even lower than established “old economy” businesses (Barker, 1995; Gupta & Wilemon, 1990; Julien, 1995; Sleeth, Pearce, & George, 1995). This is surprising because sociologists and economists predict that new ventures will be more innovative than established firms (Acs & Audretsch, 1990; Burns and Stalker, 1961; Schumpeter, 1934).

There are many studies of the causes of technology adoption (diffusion) in the literatures of economics, management science, strategic management, and organizational behavior, including those that point to performance gains from having a technology strategy. However, these studies focus on established large firms (Collins, Hage, & Hull, 1988; Dewar & Dutton, 1986; Gatignon & Robertson, 1989; Khan & Manopichetwattana (1989); Katz & Shapiro, 1986; Kimberly & Evanisko, 1981; Zahra & Covin, 1993).

In contrast, there are few empirical studies about the causes of newventure technology adoption and its effect upon new venture performance. Shane (Forthcoming) found a relation between technology characteristics (regimes) and new venture formation. Other researchers have found positive relationships between technology strategies and new venture performance in high tech ventures (McCann, 1991; Zahra, 1996; Zahra and Bogner, 1999).

The overarching purpose of this study is to find out why new ventures have been slow to adopt technology. Thus, it focuses on finding the causes of technology adoption. However, the research questions begin with a challenge to the intuition that technology adoption contributes to new venture performance. If it does not, it may be that founders have been slow to adopt technology because they have knowledge that adoption has yielded little benefit. If there is benefit in adopted technology for new ventures, then the answer to the slow adoption anomaly may lie in analysis of multiple causes of multiple types of technology adoption.

Toward this end, the research questions are: (1) Does technology adoption contribute to new venture performance? (2) What causes technology adoption? And (3), Are causes consistent across technology types? In pursuit of answers, I propose a theory of internal and external forces that affect strategic decision-making and action about technology adoption (See Figure 1). Hypotheses are tested with responses from 201 entrepreneur/CEOs of new manufacturing ventures.

This study is the first that goes beyond technology strategy to strategic action. It extends research about technology and new ventures by studying multiple technology types and performance and by focusing on adopted technologies in non-technology-based manufacturing firms. The architectural woodwork industry is the setting. In the industry, entrepreneur/CEOs have choices about the timing and intensity of technology adoption. I chose venture growth as the output concept of interest rather than other types of performance, because entrepreneurship researchers point to growth as the crucial indicator of venture success (Covin & Slevin, 1997; Low & MacMillan, 1988).

The contribution of the study is that results should help academics and practitioners evaluate five causes of technology adoption: (1) technology strategy, (2) expected cost savings, (3) customer attraction, (4) competitive threat, and (5) financial resources. The study analyzes venture performance related to: (1) product design, (2) manufacturing, (3) marketing, and (4) management information systems (MIS) technology. Thus, this project continues the search for competitive advantages that enable entrepreneurs to grow and manage their companies. The usefulness and validity of the study is supported by: (1) its six-year longitudinal design (1993 to 1999), (2) verification of CEO reports of independent variables with subordinate reports, and (3) verification of CEO reports of financial accounting performance with Dun and Bradstreet.


THEORY AND HYPOTHESES (ABBREVIATED VERSION)Technology Adoption and Venture Growth Technology adoption is the application of new science to improve products or processes. Two competing perspectives about technology adoption (the structural and technoeconomic perspectives) agree that product/process innovation improves business performance (Burns and Stalker, 1961; Hull and Hage, 1982). Indeed, Zahra and Covin (1993) found that established manufacturing companies with plans to adopt technology have better returns on sales than those without plans. Similarly, Zahra (1996) found that several new venture technology strategies are associated with venture growth and profitability. Thus, assuming that action mediates the strategy-performance relation, and that improved products/processes improve venture competitiveness, I expect venture growth to follow adoption of technology in new ventures:

Hypothesis 1: Technology adoption causes new venture growth.
Causes of Technology Adoption
The choice to adopt technology is a strategic choice that is important for business performance. The choice process may be formal or informal, individual or team-based (Schwenk, 1988). Whatever the format and structure, internal and external forces impact the outcome and subsequent action (Hamel & Prahalad, 1989). A review of management science, marketing, economics, organizational behavior, and strategic management revealed five factors that researchers believe are important in technology adoption decisions. The factors are: (1) technology strategy, (2) expected cost savings, (3) customer attraction, (4) competitive threat, and (5) financial resources (Gatignon & Robertson, 1989; Utterback & Abernathy, 1975; Zahra & Covin, 1993).

Technology Strategy Technology strategy is a company’s plan of action for acquiring, developing, and exploiting technological resources. Although technology adoption may occur in businesses without a formal technology strategy (Baum, Locke, & Smith, forthcoming), Gatignon and Robertson (1989) found that having a formal technology strategy improves business performance, and Zahra (1996) and Zahra and Bogner (1999) extended this positive finding to the new venture case. Since entrepreneurs expect their strategies to work and their strategic intentions are followed by action (Bird, 1992), I hypothesize:

Hypothesis 2: New venture entrepreneur/CEOs who have a technology strategy will adopt more technology than those who do not have a technology strategy.
Cost Savings The most frequently evaluated characteristic of strategic decision options is financial cost (Schwenk, 1988). Indeed, expected cost savings may be the most objective dimension in strategic choices and the most easily related with expected profits. Cost savings provide a powerful inside-the-firm motivation for change because they may permit price reductions that produce competitive advantage. Research has shown that cost savings are a motivator of technology adoption (McCann, 1991):

Hypothesis 3: New venture entrepreneur/CEOs who expect cost savings from technological innovation will adopt more technology than those who do not expect cost savings.
Customer Attraction Perceived customer attraction may be as important as expected cost savings in motivating technology adoption. Customers are attracted when new technology fills a product or service void, or technologies may simply improve the quality or service of existing products/services (Utterbach & Abernathy, 1975). Also, visible adopted technology may be attractive because it reveals or suggests producer sophistication, legitimacy, or modernity. Technology adoption affords new venture entrepreneur/CEOs an opportunity to differentiate themselves from established competitors (Julien & Raymond, 1994). Whatever the dynamic, customers effectively control the patterns of resource allocation in well-run companies (Christensen, 1997), and customer attraction is essential for sales and, therefore, profits (Gatignon & Robertson, 1989). Thus, I hypothesize:

Hypothesis 4: New venture entrepreneur/CEOs who expect customer attraction to adopted technology will adopt more technology than those who do not expect customer attraction.
Competitive Threat Perceived competitive threat may motivate strategic decision-makers to adopt technology, because they fear competitors will achieve cost or marketing advantages through technology. Decision-makers may even attempt to preempt a competitor’s reputed technological advantage by making similar, early, adoptions of technology (Gatignon & Robertson; 1989; Utterback & Abernathy, 1975). Researchers suggest that competitive threat is most intense in markets where a few companies dominate and cooperation is not present (Hofer and Schendel, 1978); thus, industry concentration has associated with intense competitive threat (Dess & Beard, 1984; Katz & Shapiro, 1986; Sheppard, 1985. Industry concentration may be threatening because top competitors have large resource pools and may cooperate against industry/market entrants (Blili & Raymond, 1993). I am persuaded that most new venture entrepreneur/CEOs sense and fear competitive threat and look to technological advantages for competitive advantage. Thus, I hypothesize:

Hypothesis 5: New venture entrepreneur/CEOs who compete in concentrated markets will adopt more technology than those who do not compete in concentrated markets.
Financial Resources With few exceptions, adoption of technology requires expenditures that consume free cash, untapped banker’s commitments, or untapped opportunities to raise debt or equity from private or public capital markets. The consumption of financial resources may be constrained by decision-makers’ perceptions of financial risk or by personal goals about acceptable levels of shared financial control (Gatignon & Robertson, 1989). Indeed, limited financial resources may limit growth (Porter, 1985).

Researchers have found that the interaction of investment requirements and financial resources are important considerations in strategic decisions about adoption of technology (Dowling and McGee, 1994; Khan & Manopichetwattana, 1989). Similarly, those who have studied new venture/small business investment in technology have pointed to the importance of financial resource limits for technology adoption (Julien 1995; McCann, 1991; McGrath, Venkatraman, & MacMillan, 1994). I expect new venture entrepreneur/CEOs to reflect these findings in their decisions about investment in technology. Thus, I hypothesize:

Hypothesis 6: Technology adoption will be affected by new venture entrepreneur/CEO’s evaluations of the sufficiency of financial resources.
Technology Types Technology impacts all business activities from invention/creation to delivery and customer payment. Strategic management researchers, who have focused on technology strategies, have found varying relationships with performance across technology types (Bantel, 1998; Madique & Patch, 1988; Zahra & Covin, 1993). Following these studies, I focused on: (1) product design, (2) manufacturing, (3) marketing, and (4) management information systems (MIS) technologies.

Product Design Technology Computer aided design (CAD) has impacted product/process design practices. CAD software and hardware configurations simplify drawing, storage, transfer, design change, and communication with manufacturing. This technology enables 3-D visualization of products, clear and fast electronic transmission of plans to internal and external decision-makers, and rapid modification to assist evaluation of downstream impact. Material and assembly technologies are a second form of product design technology that has simplified and lowered the cost of prototype production and broadened the array of appearance, function, and cost options available to designers. In short, product design technology has broadened options for the designer, and it has enabled higher rates of product change.

Manufacturing Technology Manufacturing has been impacted by computer-based information and communication technology, CAM (computer-aided machining) technology, material technology, and transportation technology. Information and communication technology permitted “just in time” inventory controls and production scheduling. CAM has improved production line practices to yield consistent high quality production, and it has enabled the manufacture of customized products in shorter intervals at lower costs. Small manufacturing enterprises, such as those studied here, have been implementing computerized manufacturing technologies at an increasing rate (Acs & Audretsch, 1990; Julien & Raymond, 1994; Julien, 1995). This trend is probably in response to global competition and regional competitive threat (Zahra, 1996). Also, in established industries where dominant designs have developed, such as the industry studied here, investment focus has been shifted from design aids to cost-saving manufacturing aids (Utterback, 1994). Whatever the emphasis, product design and production process technologies are increasingly integrated to achieve economies and quality. It appears that both technologies are important for market success (McCann, 1991).

Marketing Technology Marketing technologies studied here are: (1) high tech field communication tools, and (2) marketing information systems (Adoption of promotion-only and interactive websites was studied but not reported here because data was only collected in the 1998 survey.). High tech field communication tools are employed by field-based product/project managers. These technologies include laptop computers, mobile point-of-service terminals, cell-phone/beepers, and field promotion/demonstration software. The general purpose of these marketing aids is to improve the quality and efficiency of field sales and service by increasing the amount and timeliness of information that is available to the field salespersons/project managers for their customers. Adoption costs are low for this type of marketing technology in the industry studied; a field person can be outfitted with the latest technology for less than $10,000. The technologies are highly visible to customers. The causes and effects of computer-based marketing information technologies are studied as part of management information technology which follows this section.

Management Information Systems Technology MIS technologies are those computer-based applications, internal networks, and external networks that enable collection and analysis of large amounts of financial, market, and organizational data to assist management. Applications include general office suite software as well as customized internal applications for collection and analysis of sales, cost, product, inventory, production, and distribution. The purpose of MIS systems is to provide management with real-time information to assist strategic and operational decision-making. MIS researchers point to advantages offered by MIS to businesses that are decentralized or which have complex communication, coordination, and control challenges (Raymond & Pere, 1992). Thus, it may be that simple new ventures do not benefit from MIS.

Controls (Abbreviated Version) I included five controls to clarify the relations between proposed causes, technologies, and venture growth: (1) A single industry study, (2) Venture age, (3) Venture size, (4) Entrepreneur/CEO personal technical and industry specific competencies, and (5) entrepreneur/CEO motivation.

METHODOLOGY (ABBREVIATED VERSION)Field Study Participants, Pilot Study, and Questionnaire
Firms that manufacture architectural woodwork in the United States were studied (part of SIC 2431). In 1993, the industry’s 849 CEOs were asked to return a response card if they were willing to participate, and they were asked to identify a subordinate employee with whom they worked directly. I employed pilot testing with 16 of the industry’s entrepreneur/CEOs to develop test measures for a questionnaire. In 1993, I mailed a questionnaire to each of the 442 CEOs who agreed to participate and sent an adapted version of the questionnaire separately to the 202 employee-participants (EP) whose CEO had also agreed to allow such EP participation (EP responses were used to verify CEO responses.). A second questionnaire was mailed in 1999 to the 1993 CEO participants. Tests verified the representativeness of the respondents. Disqualification of respondents who did not qualify as entrepreneurs, yielded two hundred-one (201) responses from entrepreneur/CEOs (24% of the population).

Measures and Controls A measurement model table is available from the author. It shows the 29 measurement model concepts: venture growth, 4 technology types, 5 predictor concepts for each technology type, and 4 controls. The table also shows the number of measurement items, format, and LISREL 8.3 composite reliability (CR) for each concept. CR is conceptually similar to ALPHA (Cronbach, 1951); it should exceed .60 for exploratory model testing (DeVellis, 1991; Van de Ven & Ferry, 1980).

RESULTS (ABBREVIATED VERSION)LISREL 8.3 and PRELIS 2 were used to: (1) impute missing data, (2) evaluate concept validity [reliability (including dual-source similarity), convergent, and discriminant validity], (3) perform confirmatory factor analysis to verify the validity of the proposed configuration of causal concepts, and (4) test the hypotheses. (PRELIS 2 HT) and multiple sample analysis (LISREL MSA) confirmed the similarity of the response distributions of the 83 entrepreneur/CEO-EP pairs, as well as the distributions of the entrepreneur/CEOs with EPs (n = 83 ) and without EPs (n = 118).

The measurement model table (available from the author) shows that the measurement model had 21 concepts with CR > .80, 7 concepts with CR between .70 and .79, and 2 concepts with CR between .60 and .69. All measure coefficients were significant (t > 2.0; p < .05); thus, convergent validity was established. Discriminant validity was verified by determining for each latent variable that the average variance extracted by the latent variable’s measures was larger than the latent variable’s shared variance with any other latent variable (Fornell & Larcker, 1981). Common source bias was not significant according to CFA analysis with a common latent variable. In summary, the measurement model exhibited reliable measurement of the latent variables, convergence of the measures of each concept, and divergence of the concepts.

J. Robert Baum, University of Maryland

Table1
Table 1 shows the “fit” results of the structural equation modeling. All 4 technology-type models have acceptable fit statistics. For example, the poorest fit among the 4 is for marketing technology: [X2 (98) = 153 which is significantly better than the independence model X2 (127) = 1280; GFI = .92; AGFI = .88; RMR = .069; RMSEA = .088], and 46% of the variance is explained.



Table 2 shows the structural equation coefficient results. All 4 technologies are significant causes of venture growth which confirms Hypothesis 1. The controls for entrepreneur/CEO industry and technical competency and motivation impacted venture growth positively across technologies. Technology strategy and competitive threat are predictors of technology adoption regardless of technology type. This confirms Hypotheses 2 and 5. (1) Cost savings affects manufacturing and MIS technology adoption, (2) customer attraction affects product design and manufacturing technology adoption, and (3) financial resources affects manufacturing technology adoption. Thus, Hypotheses 3, 4, and 6 are partially confirmed: Support is dependent upon technology type. The size and age controls also have varying impacts upon technology adoption: (1) Product design and marketing technologies are adopted by younger ventures. (2) Larger and older firms adopt more manufacturing and management information technologies.

DISCUSSION AND CONCLUSION

The most important finding of this study is that the causes and timing of technology adoption in new ventures are dependent upon technology type. Studies that point simply to findings that newer ventures are slow to adopt technology are misleading because newer manufacturing ventures are early adopters of product design and marketing technologies. However, new ventures do hold off adoption of manufacturing and MIS technologies until they grow larger, have sufficient resources, and expect internal and external benefits. Nevertheless, the new ventures studied were committed users of manufacturing and MIS technologies at the end of the six-year study period (More than half had adopted 50% or more of the manufacturing technology and MIS technology measurement items.).

This study of actual behavior confirms that technology adoption contributes to new venture performance. The six-year duration of the study adds credibility to the proposition that the relation is causal.

My findings about adoption support those strategic management and entrepreneurship researchers who have found significant correlations between technology strategy and performance. It makes sense that adoption would also relate with performance, because it is one-step closer to performance in the causal chain that spans strategic choice and results. The findings suggest that rational planning precedes action and success in new entrepreneurial ventures.

By studying multiple causes and multiple technologies, I offer a more complete picture of the technology adoption process and outcome. Indeed, this study offers a foundation for a more complete theory of technology adoption. This study’s (1) identification of some of the causes of technology adoption, (2) finding that causes are dependent upon technology type, and (3) finding that adoption leads to venture growth should help researchers craft more complex theories and empirical studies. This study also supports my view that the strategic choice perspective offers a useful platform for identifying the internal and external forces that impact technology adoption.

The picture that emerges is of an entrepreneur who plans to be “on the cutting edge” technologically but who weighs marketplace forces presented by competitors and customers within the limits of financial resources and opportunities. Indeed, the early adoption of product design and marketing technologies found here may be evidence of choices that have been made to distribute resources to generate demand before investing in supply.

According to this study, the causes of technology adoption depend upon technology type. For example, adoption of product design technologies appears to depend little on expected internal cost savings. Furthermore, respondents report less concern about financial resources when considering product design technology investment. Perhaps, this is because product design is a first step in producing and marketing a product/process, so that new ventures must adopt associated technological aids earlier than others. That is, without external acceptance of the product design, nothing else matters. Indeed, the prime motivators of product design technology adoption were the two external forces: expectations about customer attraction and perceptions of competitive threat.

In contrast, manufacturing technology adoption occurred later in the typical venture’s life and with large significant standardized coefficients for the internal causes associated with adoption (cost savings = .41 and financial resources = .53). The adoption hold back for manufacturing technologies may also be related to the high investment required for most manufacturing technologies in the industry studied (CAM and high-tech tooling is generally more expensive than product design, marketing, and information systems hardware and software for SIC 2431 manufacturing companies.).

Marketing technology adoption was accomplished early in the new ventures studied. I was surprised that customer attraction did not appear as a significant cause. One would think that marketing technology adoption (laptop computers with 3-D display software, cell phones, etc.) would be driven by perceptions that these technologies create a positive impression with customers. Competitive threat was a significant cause; thus, it may be that marketing technologies are adopted more as a defensive move. Perhaps customers expect these technologies rather than seek them out. In short, marketing technology adoption may be essential, not optional.

Management information system (MIS) technology adoption followed timing patterns that were similar to manufacturing technology adoption patterns: Adoption occurred later when the new ventures were larger. It may be that there is no significant benefit from these technologies until scale is achieved (For example, computer networks are of little value in firms with few employees.). It may be that founders delay adoption because adoption is organizationally disruptive. It may be that customers do not care about these internal practices. Whatever the cause of the delayed implementation, this study pointed to two motivators of MIS adoption: expected cost savings and competitive threat.

LIMITATIONS

Analysis of a single industry provided control of industry effects and may have added richness and clarity; however entrepreneurship researchers have found that industry characteristics affect venture performance (Shrader & Simon, 1997; Shane, forthcoming). Thus, these results may not generalize to other industries.

Although I reviewed literature from multiple domains in search of likely causes of technology adoption decisions, I may have missed important personal, organizational, and environmental causes. Finally, venture growth may not be a sufficient indicator of venture performance. Indeed, researchers point to the importance of successful founding, founder satisfaction, profits, and other indicators of performance not studied.

In conclusion, the model of the causes of technology adoption presented in this paper offers a platform and framework to guide those who make strategic decisions about technology. The specific findings about the varying importance of technology strategy, expected cost savings, customer attraction, competitive threat, and financial resources in decisions about adoption of product design, manufacturing, marketing, and MIS technologies may help those who teach courses about technology, and researchers who are forming more complete theories about technology.

CONTACT: J. Robert Baum, Smith School of Business, University of Maryland, College Park, Md. 20742; (T) 301-405-9308; (F) 301-403-4292; jrbaum@rhsmith.umd.edu

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