Rosan,

I've now read your question carefully (this email only) and several times. This is what your research design requires if you are posing this as en empirical question:

1. "my reading of popular and professional accounts of the success of Apple under Jobs"

That is a discourse analysis, and one helpful approach is predicate analysis. Your universe of relevant material will be defined by the criteria you set, i.e., popular and professional accounts. You will need to define those terms and and explain why these definitions are productive and generative in answering your question. Your answers will NOT be the only answers available. Rather, they need to show fidelity between your question, your modes of analysis, and the claims you will be making from your analysis. 

You also have a nicely available timeline for your analysis (i.e. under Jobs). 

2. You are going to need to independently measure the success of Apple under Jobs. There are many, many ways to do this, but here are some of the key conceptual matters you will need to attend to: How are you measuring success? Revenue? Year-end accounting? Market share? Capitalization? Relationship of their strategic goal to their achievements, and therefore you're using an in-house measure? One way or another, this needs to be answered and quantified over time.

3.. Whatever the measure, you will now need to make a claim about the status of that level of success. And the only way to do this that I can think of is comparatively. So compare "like to like." I'm not an expert in this business area so i don't know the answer. But I need to see at least several time series lines showing a "measure of success" for these 2/3/4/5/ companies. And they should be co-terminous (sorry for the pun) with Job's tenure at Apple.

4. And you will then need to do another discourse analysis of the "popular and professional accounts" of these other companies.

You eventually arrive at a series of measures of success that can be compared to measures of reputation grounded empirically in discourse analysis. 

You will then be able to look across the cases and say, "yup, Apple was definitely perceived to be doing better than rivals that were, in fact, doing just as well." Or not. I have no idea. 

You will still be in NO position to explain WHY any of this might be true. You will also be in no position to talk about the "tendency of journalists" to support their theories using Apple, because you didn't code the data for "theoretical claims by journalist" which is harder, but possible with the same data set. But even there, you'll need to separate out "journalists" from "popular and professional accounts" , and then creating a sub-set that identifies those who put forward theoretical claims and mobilized the "success" of Apple under Jobs to explain it.

Good luck with the study. I look forward to the results.

Derek Miller


_________________
Dr. Derek B. Miller
Director

The Policy Lab
321 Columbus Ave.
Seventh Floor of the Electric Carriage House
Boston, MA 02116
United States of America

Phone
+1 617 440 4409
Twitter
@Policylabtweets
Web
www.thepolicylab.org 

This e-mail includes proprietary and confidential information belonging to The Policy Lab, Ltd. All rights reserved.

On Feb 3, 2012, at 10:55 AM, Rosan Chow wrote:

> Hi Ken, 
> 
> I am glad that you were amused and thanks again for replying. Although it will take away the amusement, it is useful to contain the general question in the context which it arises.  To repeat: the context was my reading of popular and professional accounts of the success of Apple under Jobs. I wanted to know whether the impression I got from the reading was correct and whether this impression represented a more general problem among researchers who study successful business / management / innovation / engineering / design cases. So my question is more specific than you have taken it to be. 
> 
> My impression was that there was a tendency for the journalists, bloggers, or even researchers to read or use the success of Apple to support their theory or point of view. 
> 
> I am aware of the values and difficulties of case study research and I know Nonaka’s work a little bit. And precisely because of this background knowledge, I was even more struck to find that despite the theoretical discussion and careful analysis (which of course sets apart his paper from other more casual commentaries) , this particular paper of his left the same kind of impression mentioned above. 
> 
> He probably has done more work since to substantiate his theory of innovation management and I am not at all questioning his theory (which I actually like but this is not the point). I am curious:  in this particular paper he used the cases studies to support his theories without, in my judgment, the kind of robust argument that you said needed for an ex-post facto analysis. For a positivist account of good theory building from Case Study research, I have located this paper: 
> http://intranet.catie.ac.cr/intranet/posgrado/Met%20Cual%20Inv%20accion/Semana%203/Eisenhardt,%20K.%20Building%20Theories%20from%20Case%20Study%20Research.pdf
> 
> However, my focus is not on evaluating Nonaka's paper, but rather on my impression stated above. I would be happy to hear that my impression is not correct and there is no problem at all in the research on successful cases and Nonaka’s paper was written this way because it was at the beginning of a theory building or whatever …. I am completely open ...but I would appreciate some pointers. 
> 
> Many thanks. 
> rosan
> 
> 
> -----Original Message-----
> From: Ken Friedman [mailto:[log in to unmask]] 
> Sent: Donnerstag, 2. Februar 2012 13:34
> Subject: Re: Is claim/research on 'success' one-sided? RE: Apple Success under Jobs
> 
> Well, I’m just sitting here laughing. This is the big question: “is there a genuine problem when it comes to ex-post facto analysis of successful? If yes, how is it overcome in research?”
> 
> As history, all analysis of cases is ex post facto. No one can properly isolate all the key variables in historical analysis, and no one can re-run historical cases to see whether alternate choices would actually have made a difference. 
> 
> On a limited basis, one can attempt to simulate the effects of minor differences in situations where one can analyze and conceptually isolate those differences, but there is no way to be sure. 
> 
> The way through this is robust, reasoned analysis. Nevertheless, historical analysis – including the historical analysis of business cases – always involves judgment calls. 
>