ฝึกพูดภาษาอังกฤษด้วยเทคนิค Shadowing จากวิดีโอ: Decision-Making and Entrepreneurial Performance: Evidence from a Field Experiment
กำลังสร้างบทเรียน...
1
thank you thank you very much ryan can you hear me and can you see the slides perfect
2
perfect thank you so much so i'm elena novelli from base business school
3
and as you mentioned today i'm presenting we are presenting together with chiara from inside this paper
4
and we would like to first of all thank sms for organizing this session we are delighted to be here
5
and also i can see there are many friends in the audience
6
so thank you
7
so much for taking the time to attend our presentation we
8
are really at a stage where we would certainly benefit from feedback
9
and comments so we look forward to hearing from you later
10
so this paper builds on the observation that innovation settings
11
and entrepreneurial settings in particular are characterized by a high degree of uncertainty
12
so part of which is endogenous to firm action
13
so a very important question in these settings is how can firms navigate this uncertainty
14
and in particular what kind of decision -making processes can help them navigate uncertainty.
15
So if we look at prior research there are essentially two main approaches
16
that have been identified that can help firms navigate uncertainty.
17
First of all what we can call a cognitive -based approach.
18
A cognitive -based approach is essentially based on the idea of addressing uncertainty by reasoning through theory,
19
frameworks or rules that can help decision makers understand what to do.
20
Alternatively, decision makers can use what we could call evidence -based approaches.
21
These approaches are essentially based on the idea of addressing uncertainty via the systematic collection of evidence and its discipline assessment,
22
with the idea that in this way they can learn from the environment.
23
Now, more recent evidence has suggested that there are actually important synergies that exist between cognitive and evidence -based approaches.
24
For example, the work of Cathy Eisenhardt
25
and Chris Bingham suggests about the importance of combining thinking and doing to devise superior strategies.
26
Or, for example, the work of Rory McDonald and Cathy Eisenhardt shows that entrepreneurs who combine cognition with evidence,
27
for example, using experimentation to test the key assumptions underlying a business model, can accelerate their learning.
28
Or finally, the work of Camufo and colleagues shows the benefits of a scientific approach to decision making,
29
an approach that combines elements of cognition, as well as elements of experimentation.
30
So we use the terminology used by these authors,
31
and we will talk about the scientific approach to decision -making to refer to an approach that uses theory,
32
hypothesis, but then tests these hypotheses with evidence and conducts a discipline evaluation of that evidence.
33
The expression scientific approach refers to the fact that approach that uses theory,
34
hypothesis, evidence and evaluation really resembles that used by scientists in the development of knowledge.
35
Now, let me give you an example about how such an approach might actually work in practice, especially in the context of entrepreneurial decision making.
36
So here is an example of an entrepreneur we worked with.
37
Essentially, this entrepreneur identified and developed a theory about the fact
38
that there is actually some unmet demand in electronics that comes from non -tech savvy consumers.
39
These consumers are really more interested in the usability of products, in the aesthetics of products.
40
They don't really know the details about the technical specifications.
41
So they know what they want to achieve, but they don't know exactly what technical specifications they need to achieve that.
42
So this entrepreneur developed a theory about these types of consumers
43
and how their demands could be met and developed a set of hypotheses.
44
An example of one of these hypotheses was,
45
for example, that providing customers with information on product compatibility was more relevant
46
when they were making a purchase than providing them with very detailed technical specifications
47
so they devised a set of tests to for their hypothesis
48
and for example in this case they ran an online test
49
and a b tests for two weeks offering customers different product
50
specifications on the one hand information about product compatibility on the
51
other hand information about technical specifications of products they found
52
that their hypothesis was supported and so
53
So they continued iteratively to test hypothesis about their theory until
54
they reached the stage where they developed a very solid and robust value proposition that enabled them to grow and succeed. So...
55
Let me synthesise what a scientific entrepreneur is.
56
A scientific entrepreneur is one who starts with a mental model that explains how a business creates value.
57
He or she then proceeds to articulate, to decompose that theory into testable propositions that logically flow from the theory.
58
They then perform rigorous tests with representative samples of customers, and then they assess the evidence collected in a disciplined way.
59
If this is a scientific entrepreneur, who is then a non -scientific entrepreneur?
60
A non -scientific entrepreneur is one who draws conclusions based on testing, but with no counterfactuals.
61
It's someone who tests multiple versions of a product, but without being driven by a theory.
62
Therefore, there is a higher degree of causal ambiguity.
63
Or someone who performs lower quality tests, for example, multiple versions of a product or a service are tested, but they differ more than one characteristics.
64
So the signal that those tests can reveal is certainly more noisy.
65
So the key research question that this paper addresses is to what extent
66
and under what conditions is a scientific approach to decision -making,
67
so an approach that combines cognition and evidence, associated with superior performance.
68
And in particular, what we want to understand is whether a scientific approach can benefit all firms equally.
69
Now, we believe that this is a very important question, especially because the main evidence
70
that has identified a positive relationship more in general between systematic decision -making approaches
71
and performance tends to be focused on more established firms.
72
So we want to understand this question more closely.
73
Thanks, Elena.
74
So this leads us to the focus of the paper, which is how do we expect the scientific approach to impact the performance of entrepreneurial firms and of different firms in particular?
75
So we're going to look at the impact of a scientific approach on performance first.
76
If you could please go to the next slide.
77
And we have a baseline hypothesis.
78
What we are expecting building on literature on strategy, entrepreneurship, decision -making, and organizational learning is that overall,
79
the scientific approach will improve this process of iteration that entrepreneurs usually go through.
80
This will result in better decisions and in better performance.
81
And we expect this because we are considering what the scientific approach does as entrepreneurs are making decisions.
82
On the one hand, as Elena was describing, the scientific approach is very beneficial
83
because entrepreneurs have a mental model they have a theory
84
and this implies that they have a clear representation of the problem they're facing and they're then able to articulate hypotheses
85
what theory and hypotheses do is
86
that they lead to more precise tests they're basically spotlighting what are the key assumptions
87
that entrepreneurs have and that they need to test in order to make sure
88
that a business is viable now this increased precision results in tests
89
which are more focused and therefore are more likely to result in learning in addition to
90
that the entrepreneurs are also gathering evidence
91
that they are evaluating in a very systematic manner and
92
so what evaluation does is
93
that it helps entrepreneurs first of all understand whether the evidence is supporting their initial assumptions
94
but also it's very beneficial when entrepreneurs do not find evidence actually support their hypothesis
95
which happens quite frequently and when that is the case the fact
96
that entrepreneurs have a clear framework is actually very beneficial in helping them in understanding what to do next
97
so for these reasons we're expecting
98
that the scientific approach will have a positive effect on decision making
99
and performance now we are also interested as we mentioned earlier in understanding what happens with firms
100
that are different levels of business development and what do we mean by that
101
we have looked at the literature and interestingly
102
when it comes to entrepreneurship entrepreneurship Entrepreneurship is often thought about as a journey
103
that requires firms to go through various steps and go through an evolution process.
104
So you can think of an entrepreneurial firm as some scholars have used the parallel of the human life.
105
So when a firm is born, like a baby, it's not fully formed.
106
It's in a very embryonic stage, if you will, which we can consider the startup phase, which is also described as a progressing nascent venture.
107
But this can progress over time, going all the way to a more established phase where the firm becomes a more sustainable and continued market participant.
108
Now, the reason why this level of business development, and this is the construct that we're focusing on here, is particularly important is because these firms are in fact facing different problems.
109
The fact that the firm is more or less developed actually implies that they've conducted slightly different activities, but they're facing different problems.
110
And the fact that they're facing different problems has important repercussions for the type of decisions that they're making.
111
to make this a little bit more concrete let me provide some definitions and also give an example
112
when we are looking at firms that are lower level of development
113
and remember that this concept is a continuum so the example
114
that we have here is just a simplification
115
so we're providing an example of a low and high level
116
but of course there is a continuum you can think of
117
a firm with a low level of development as a firm
118
that is still quite early on in the process of venture creation and
119
so doesn't have a particularly well -defined value proposition just yet
120
on the other hand of the spectrum you can have a firm
121
which is at a higher level of business development meaning
122
that it's later on in the stage of development as a firm
123
and this means that the value proposition is more defined and
124
so the entrepreneur is more fine -tuning this value proposition now to be very specific let's look at an example
125
and the example that we have here is one simple business idea help busy individuals stay fit
126
so these are people who usually don't have time to go to the gym
127
or attend some classes so you can have an entrepreneur
128
that is trying to develop this business idea and here we have images
129
that represent these two different levels of development on the left
130
hand side what you are seeing is the low level of
131
development where the entrepreneur has not decided yet how she's going
132
to deliver this value to the customer this could happen through sessions
133
which are close to for instance a park where the person lives they could be delivered online
134
or they could be offered through a gym in a van on the right hand side what you're seeing is
135
that the entrepreneur instead has decided
136
that the offer will happen through a gym in a van
137
and so this gives you a sense of what it means to have a more
138
or less developed business idea now what this does is
139
that it implies
140
that these firms as we were talking earlier about the level of development are facing different problems And in particular, when we're looking at firms which have a lower level of business development,
141
they're facing broader problem.
142
By their very own nature, these problems are more open, they're more complex, there are more aspects that need to be taken into account.
143
So in this case, what we are expecting, building on literature on organizational learning in particular, is that there will be more ambiguous learning and a slower pace of feedback,
144
which is something that usually happens when actors are dealing with problems, actions, and consequences, which are quite broad in scope.
145
As a consequence, this implies that it's going to be harder for these entrepreneurs to learn
146
because the information that are emerging will be noisier.
147
On the other side, when we're looking at a higher level of business development instead, what happens is that these firms have different types of problems
148
that they're facing they are narrow in scope and what happens
149
when actors are facing narrow problems is
150
that the process of decision making is simplified and this implies
151
that it will be easier for these entrepreneurs to apply the scientific approach
152
and here you can think of some studies like eti raj
153
and levin tall but also philip xsr that show how
154
when you simplify this landscape of decision making for instance by keeping some aspects of decision making constant
155
and just varying some aspects of the problems to change then these results in simplified processes of decision making
156
and more effective decision making so the argument is
157
that there will be enhanced learning for these firms
158
which are the more advanced level of business development and
159
so for these reasons we're expecting
160
that the level of business development is moderating positively the impact of a scientific approach on performance
161
how do we test these ideas well we ran a field
162
experiment as it was alluded to earlier with the title
163
and we use actually business support program to run this experiment
164
you can see some pictures here from the study you can
165
see elena myself the entrepreneurs the program were broadly it was a project
166
that was made possible thanks to generous funding from the uk government
167
which allowed us to create a program just for the purpose of this particular study
168
and this meant
169
that we recruited research assistants instructors in we created a demo
170
day with investors i'm going to provide a little bit more details about
171
that but most importantly we have firms
172
which are at various level of business development participating to the
173
study here's our review of the rct uh is i'm just
174
going to provide some high level details of the study of course there are a lot of details with experiments, so feel free to ask any questions that you might have.
175
What we did is that we started off with a call for applications.
176
So we created a website and we started a marketing campaign.
177
We managed to recruit 261 firms.
178
After that, we randomly allocated them to either treatment or control condition.
179
And what's important to point out here is that they both attended training.
180
Both groups received the same amount of training for the same amount of hours with the same instructors on the same topics.
181
The only difference is that 3D entrepreneurs learned about a scientific approach and entrepreneurs in the control group didn't.
182
As a final step, we conducted data on these entrepreneurs for about 10 months using some phone interviews, as we're going to show you more details.
183
This is a slide that gives you a sense of the timeline of the project.
184
The project overall from design to end lasted for 12 months, but here what you can see is that we started off the training in month one,
185
which was February 2019, and we ended in April 2019.
186
During this time, we had 21 hours of training split over seven sessions, and this is where the treatment was.
187
After that, until December 2019, we had monthly events.
188
The monthly events were exactly the same for the treatment and the control group.
189
We actually ran the same event twice on different days
190
or different times of the day to prevent these people from talking and potentially disclosing elements of the treatment.
191
As you can see, the data collection goes on from right before the treatment started all the way until the end, which was December 2019.
192
to give you a little bit more details about the participants what we did as i mentioned we recruited firms
193
that were at different levels of business development there were no prerequisites in terms of industry
194
so we ended up with a beautiful variety in terms of the type of businesses
195
that attended the program from those that were interested in fashion retail fintech
196
security environment education really different type of businesses what they all
197
had in common however was the size of the firm they all the firms could have at most 10 employees
198
and the reason why we made that particular choice is
199
that we actually wanted whoever participated into the program to be
200
heavily involved in the decision making process of the firm
201
and this condition is more accurately met in the context of these small firms the table
202
that you're seeing on this slide is showing the balance checks
203
so as i mentioned after recruiting these entrepreneurs we collected some data on the firm
204
and then we use this to check whether the randomization actually resulted in balanced groups
205
and what this table is showing you is
206
that there are no statistically meaningful differences on a range of covariates
207
which is looking at both aspects which are more demographic
208
when it comes to the firm such as what's the age the team size what's the gender ratio within the company,
209
to some which have more to do with decision making and performance.
210
To give you some details about the treatment versus the control condition,
211
as I mentioned earlier, we use the training in the same way for treatment and control firms with one important difference.
212
You can see that both the control and the treatment group are exposed to strategy frameworks, for instance, the business model canvas or balance scorecards,
213
and also data gathering techniques.
214
And so this includes, for instance, how do you run a survey?
215
How do you conduct A -B testing?
216
How do you talk to your customers?
217
How do you conduct good customer interviews?
218
The only difference is that the treatment group was also taught for each of these topics
219
and each of these sessions to use a scientific approach to decision -making.
220
And so what this meant is that for each step, they had to have a very clear theory of a mental model that explain how their business generates value.
221
They had to then develop hypotheses or testable propositions to test what their key assumptions were, and then conduct tests in a rigorous manner and evaluate the results.
222
So to give you a better sense of how we did this in practice, the classes were highly experiential.
223
So we had usually a fairly long lecture, so it was around one hour, one and a half hour.
224
We had various in -class activities to really make sure
225
that the entrepreneurs would understand the content that was explained to them right away
226
and we got them to apply the content of the course to their business right away
227
so the session also included some time for the entrepreneur to apply this content to their business
228
and their business idea while they were in class
229
and clarify with instructor whether they have any questions in the
230
case of the first session where we teach the business model canvas for instance what we did is
231
that we teach the business model canvas to both groups they
232
conduct the same activities however there is a difference in how they're taught to use the business model canvas.
233
control group follows a more standard approach
234
which is used in a lot of universities and accelerators
235
and business schools as well where they learn to use the
236
business model canvas as a representation of their business where various elements should be connected between them
237
and it contains some elements
238
that will be tested later on in the case of the
239
scientific approach they still learn about the business model canvas however they learned
240
that that represents the basis for their theory of their firm
241
and so they are asked to also
242
and taught how to write a theory from their business model canvas
243
and they consider each element of the business model canvas as hypothesis
244
that will be tested at a later stage
245
and then we follow this logic
246
and implement similar changes throughout the course to make sure
247
that the content remains the same but the only difference is the scientific approach
248
and uh to give you also a little bit more details about the data collection process what we did is
249
that we follow an approach which was championed by bloom
250
and renan in economics with their study of management practices where
251
we decided to conduct telephone interviews with the cell phone interviews we had a team of research assistants
252
that were extensively trained on a predefined interview script.
253
All interviews were recorded and this was helpful for us to make sure that we could provide feedback to the research assistants.
254
And all these interviews ran for about once a month from February until December 2019.
255
And the research assistants were asking entrepreneurs about various topics.
256
There were both some close -ended questions
257
that were primarily measuring performance such as how many revenue did
258
your business generate in the last month what kind of cost
259
did you make any changes to your business as we're going
260
to see in in the next few slides with the results
261
and then there were some more open -ended questions as well
262
which aimed at measuring more the decision -making process that the entrepreneurs were going through
263
i think this is the end of the design part so i can leave the floor to elena for the results
264
Thank you.
265
So let me give you an overview of what we find.
266
So the first question that we wanted to address is whether treated entrepreneurs achieve better performance.
267
So when it comes to estimating performance,
268
prior research has extensively documented that firm performance is not a unidimensional construct
269
and that difference performance measures really capture different nuances of performance
270
so when we look at performance we look first of all at revenue as an established measure of performance
271
but we also look at firms growth and
272
because we know from private work that some firms focus on growth first
273
because by doing this they basically go on a better performance trajectory
274
so we wanted to capture both effects and
275
so we wanted to capture both dimensions
276
and therefore we look at both our analysis follows a classic
277
difference in different specification we therefore estimate our performance variable as a function of treatment post
278
which is an indicator variable that is valued as one for firms after the training
279
and the interaction between the two so here what we see is
280
that when we look at size of firms actually uh what we find is
281
that the treatment had a positive effect on perform on performance
282
as measure as growth in particular about a 12 % increase on performance.
283
However, interestingly, if we look at revenue, we see a non -significant effect.
284
Now, in looking at these results, we must acknowledge that our observation window was quite limited,
285
about 10 months, which is not necessarily a huge amount of time for a firm to observe a change in performance.
286
Now, ideally, we would want to observe a longer time horizon
287
that this was not possible at the moment due to obviously finding funding constraints.
288
However, to the extent that, as prior research has suggested, growth can be interpreted as an early performance measure,
289
we could interpret this result to indicate that firms
290
that are treated are led to invest in the size of the firm by hiring more employees
291
and investing in the business model
292
and this might later on lead them to achieve a superior performance in terms of revenue as well.
293
But we will go back to this point as we see more results.
294
We move next to try and understand the extent to which the scientific approach benefits all firms equally.
295
So what we do here, we use a triple difference specification, so we want to see whether the stated difference
296
that we observed between the performance before and after the treatment for treated and controlled firms,
297
how it is shaped by our
298
key variable which is the degree of business development so what we see here was that
299
if we look at different types of firms a different degree of development
300
if we look at firms more developed the treatment had an additional incremental effect on their size so
301
if we observed a impact of the treatment on the size
302
of the firm of about 11 percent what we see here is
303
that one standard deviation increase in the degree of business development
304
leads to an additional three percent increase in the size of
305
the firm what is extremely interesting for us is to observe what happens
306
when we look at revenue so you will remember
307
that we didn't find a significant effect of the treatment on performance as measured in terms of revenue.
308
Now, if we make now a distinction between firms at a low level of business development
309
and firms at a high level of business development, what we see is really interesting.
310
We see that for firms at a very low level of business development, the treatment actually had a negative effect on revenue.
311
In particular, a negative effect of about 30%.
312
On the other hand, if we look at the case of firms with a high degree of business development,
313
the treatment had a positive effect. In particular,
314
one standard deviation increase in the degree of business development is associated with a substantial increase in the performances measured in revenue,
315
a 60 % increase, which is obviously quite substantial.
316
Now, the way we interpret these results is the following.
317
We interpret these results to basically indicate that for less established firms, the method brings them back to the drawing board.
318
And so they start using the method to work again on their business model, to work again on their value proposition,
319
to change things, to do things perhaps differently.
320
And essentially, we see these being represented by the fact that they invest in their company by growing the number of employees.
321
However, they are not yet at a stage, an exploitation stage, where we see an impact on revenue.
322
On the other hand, if we look at more established firms, these are at a stage where they are already in an exploitation phase in their business model.
323
So they use the method differently.
324
They use the method to fine tune their value proposition
325
and make even more revenue and make it even and make it basically even more successful.
326
Now, this is very much in line with the findings of other scholars.
327
For example, if we think about the work of Joshua Gantz,
328
Scott Stern and colleagues, they suggest in line with these results that when firms are still in an early low commitment phase,
329
any positive signal leads them to an exploration search phase.
330
While when firms have already made significant commitment, a positive signal leads them to higher exploitation.
331
Now, these results are also robust to winsorizing alternative measures of development and fixed effect specification.
332
In a way, looking at comparing what happens to firms at a low degree of business development
333
and firms at a high degree of business development helps us
334
perhaps providing an answer to our earlier question about what happens in the longer term,
335
because what we see here is a comparison between firms that are at a different stage of the journey.
336
So this gives us a sort of snapshot at different points in time, which might suggest that in the longer term,
337
the method also helps firms exploiting and benefiting in terms of revenue.
338
More in general, we are also in conversation with the government to explore the
339
possibility of observing these firms in the longer term by basically having a longer time horizon,
340
by merging our data with the data collected by the government.
341
So this would answer our question regarding longer term even more extensively of course meanwhile we had a relevant shock
342
which was of course the pandemic
343
but this might also offer some the interesting opportunity to see whether the methods made these firms for example more resilient
344
Let me show you also some model free evidence
345
that might give us another snapshot of what happens if we look at the data.
346
So what we have here on the left hand side is
347
the average of revenue at the baseline for firms at a low degree of development,
348
lower than the average, and a high degree of development, higher than the average.
349
And we compare control and treated firms.
350
So what we see here is
351
that the revenue of firms at a low degree of development were very similar in the control and in the treatment group.
352
And also the revenue of firms at a high degree of development were very similar for the control and treated firms.
353
If we observe the averages of the revenue at the end of the period, we basically see that, of course,
354
all the revenue of all firms grew, but in the low development group,
355
firms in the control group grew more in terms of revenue compared to treated firms,
356
while the opposite is true in the case of firms at a higher degree of development.
357
So this provides us another snapshot of the results that we showed in our econometric analysis.
358
Now we are at a stage where we are trying to provide more evidence
359
about the mechanism that we suggest are behind our results and that we mentioned earlier.
360
So what we have started looking at is we asked the entrepreneur before starting our program, what were the issues that they faced?
361
And what we see is that the issues
362
that entrepreneurs at different levels of business development face are indeed different as predicted by our theory. In particular,
363
we've seen that firms at low levels of business development are significantly more likely to indicate at the baseline
364
that the main issues that they face are related to product development
365
or to the identification of the product market fit and really to the market validation.
366
So they're really facing higher level questions which concern the nature of the business model and the value proposition.
367
On the other hand, firms at high levels of business development were significantly more likely at the baseline to indicate
368
that the main issues that they were facing were relating to expanding the business and customer base.
369
So this is very much in line with our interpretation of the findings
370
that the scientific methods helped entrepreneurs at a lower stage of development to address questions
371
that were probably broader and that concerned the value proposition.
372
But in line with this, the outcome of that application, the method didn't necessarily lead them to obtain immediately revenue,
373
but probably to improve their business model,
374
to grow their, like the strength of that business model as represented by an increase in the number of employees.
375
Similarly, we are also conducting some text analysis regarding the way in which these entrepreneurs talked about their value proposition at the baseline.
376
And what we are seeing is
377
that entrepreneurs at a lower degree of business development were significantly
378
more likely at the baseline to describe their value proposition in a way that expressed a higher degree of uncertainty and hesitation.
379
We also try to provide evidence of the mechanisms by looking at what these entrepreneurs do after the training.
380
In particular, we look at the extent to which they make changes to their value proposition.
381
To do so, we use the business model canvas as a way of representing the entrepreneurial business model.
382
And I'm sure that this audience is quite familiar with the business model canvas
383
and the fact that it's composed by different elements, for example, the value proposition, customer segment, customer relationships, and so on.
384
So we look at whether entrepreneurs made any changes during the observation window to any elements of the business model canvas.
385
And we also look at the extent to which these changes were radical versus incremental.
386
And consistently with our theory and our interpretation of the results, what we see is
387
that firms at a high levels of business development are significantly more likely to engage in incremental versus radical pivot.
388
Once again, in line with the idea
389
that entrepreneurs at a low stage of development use the method to go back to the drawing board
390
and reconsider the way they're doing business.
391
but this does not necessarily lead them immediately to observe revenue.
392
On the other hand, firms that are at a more advanced stage of development have a more established value proposition, so use the method to improve it, to fine tune it.
393
And so they're already making revenue and this leads them to essentially make even more revenue.
394
We also try to exclude alternative explanations. For example, one that we consider was that maybe these results
395
that was associated with a higher
396
or lower degree of this development was perhaps driven by the experience of entrepreneurs in the industry
397
or experiencing running startups or managerial experience.
398
But none of these explanations was related to our results.
399
None of these alternative explanations essentially held.
400
Alternatively, we thought maybe this is is confidence that is really driving these results.
401
Maybe the more developed firms are more confident and so maybe this is what is actually driving our results.
402
But once again, we also ruled out this alternative explanation.
403
So to conclude, what we find is that overall
404
treated firms grow more than control firms and
405
if we look at the distinction
406
when it comes to performance as measured in terms of revenue
407
if we look at the distinction between less developed
408
and more developed businesses what we see is
409
that less developed business actually for them the treatment has a negative effect on performance
410
but it has a very positive effect on performance for more developed businesses now we believe
411
that these results show um contribute to existing literature on decision making
412
and strategy by showing an important boundary conditions for the application of the scientific decision making approach
413
and more in general about systematic approaches to decision making
414
and in particular it also highlights the complementarity between between the development of a theory about the firm and experimentation,
415
which is in contrast with the idea that entrepreneurs can really delay important choices and experiment at any stage of their journey.
416
We also believe that these results have important practical implications and they provide actionable tools for entrepreneurs.
417
We are in the process of developing some case studies as well and tools for entrepreneurs.
418
And we also believe that there's an important practical implication
419
that is particularly dear to us as educators in addition to being scholars,
420
which is basically that these results show that it's not just the content
421
that we teach in the classroom that makes the difference, but it's also the way in which the content,
422
it's also about teaching students or entrepreneurs how to use that content.
423
Because if we think about it, what we delivered in our control classroom was very similar to what we deliver in any management course.
424
But the difference in the treatment in this case was really about teaching entrepreneurs not only the tools, but also how to use them to develop a theory,
425
how to use them to test the theory.
426
So we believe this is something that is relevant for us as educators.
427
So what are the next steps?
428
We have presented today this paper, but this paper is really a part of a larger project
429
titled Scientific Approach to Innovation Management that we are conducting together with Alfonso Dambardella, Arnaud Camufo and other colleagues at Bucconi,
430
at the University of Maryland, at Erasmus, at the University of Lisandes, at the India School of Business, Coen University and Shanghai University.
431
More in general what we are trying to do with this project is
432
that of understanding and answering a broader question
433
which is what type of decision -making processes can help firms navigate uncertainty
434
and we hope with this project to be able to explore the antecedents associated with these decision making processes
435
and the implications
436
so we are in the process of setting up multiple randomized
437
control trials in different countries italy the netherlands uk colombia brazil china india
438
and tanzania and we hope
439
that this will give us the opportunity to further validate the robustness of the results
440
but also to explore other nuances and boundary conditions to improve our knowledge.
441
about decision making in the context of uncertainty.
442
So I would like you to thank you very much
443
and I will pause here and look forward to any feedback and suggestions.
444
Thank you.
445
So Elena, we actually have one question in the chat
446
so maybe we can start with that one and in the meantime
447
if people think about any other questions we can take them um
448
so since we are live online ziyan would you like to unmute yourself and ask the question
449
oh yeah can you hear me yes we can all right yeah thanks elena
450
and the care for the wonderful research is very interesting
451
and rigorous so i just have a quick question regarding the h2 uh especially in terms of the theory
452
so i think the research argument now centers on the benefits of scientific approach
453
but it also has the cost side of that approach for
454
so for the higher development of business it also means
455
that it's more costlier for them to do to adopt
456
that approach because they have larger sum costs if they use that approach.
457
So I wonder if
458
that also means the higher development also means they are unlikely to employ a scientific approach in reality
459
and that will also lead to the opposite prediction.
460
So it's about whether they use it or not rather than the approach is beneficial or not.
461
Thank you for this question.
462
We also look at costs actually in some supplementary analysis
463
and what we see is
464
that indeed the scientific approach leads more developed firms to basically higher expenses
465
so it is more expensive like they spend more
466
when they use the scientific approach so this is in line with with the prediction
467
that the scientific approach leads to higher costs not necessarily higher sunk costs but certainly higher costs
468
We also look at whether the value added, so whether, essentially, because we see an increase in revenue, and we see an increase in cost,
469
so a follow -up question could be, is it possible that increasing revenue is simply driven by the increasing cost, and so the value is simply transferred to the customer,
470
there's no value retention for the firm, and what we see is that we see an effect on value added.
471
So the scientific method leads more developed firms to also generate more value, which we believe is quite interesting.
472
I hope that answers your question.
473
Let me also add something about, right, because I think Elena was writing in talking a lot about empirics, but this is also a conceptual point, right?
474
And so the literature that looks at business development is really emphasizing how the level of development is not related to, for instance, age or cost.
475
So, of course, I think the example
476
which we showed might have primed you in that way because that shows two extremes on the continuum.
477
But usually the level of development is really about what are the problems that these firms are facing.
478
And so costs, and especially some costs which are irreversible, might not really be central in that particular case.
479
But I think it's interesting what you're pointing out about sort of what is the cost of using a scientific approach,
480
right? so i think this is also a very interesting question for for future research i see
481
that we also have a we have a question in the chat
482
and we have a hand raised and i believe
483
that the hand was raised first so why don't we hear from alexander
484
we can all hear you Alexander
485
oh it was a mistake okay
486
so there is another question in the chat from Alfonso Alfonso
487
would like to mute yourself okay just very simply uh i
488
would be curious to know how do you rule out
489
that higher developed firms are not just more skilled or experienced to adopt the approach
490
okay thank you for the question so um what we what we look at is um whether the experience of
491
more developed firms i mean obviously more developed firms are also tend to be uh more experienced
492
and we we basically uh try to see whether the effect
493
that we observe is is explained by experience whether experience leads to the same outcome
494
and we don't see So we don't find that more experienced firms
495
have a positive and more positive um like result when they use the approach
496
on the other hand when we look at the level of development we see the effect
497
does that answer your question yes thank you
498
I see Addis being spotlighted.
499
Addis, do you have a question?
500
Yes.
501
I actually left a question on the Q &A part.
502
There's a chat, so I think it was not clear.
503
It was an interesting presentation.
504
Do you hear me?
505
Can you hear me?
506
Yes.
507
Hello.
508
Hello.
509
Good to see you and it is an excellent project
510
so I have just one simple clarification question so
511
when you go on the post hoc analysis identifying the mechanisms you mentioned a few mechanisms
512
that kind of distinguish less developed and more developed businesses
513
and it felt to me more like they are the characteristics of the business themselves than mechanisms
514
so I was kind of yeah can you say a little more, as you say, in less developed business ideas, you know, owners were not very sure,
515
they had certain uncertainty, and I felt that was the very definition of less developed business idea.
516
So how do you kind of differentiate between the nature of the business idea itself, so it's not developed, versus the mechanism by which,
517
you know, the treatment helps them to, you know, to perform better? so just to check
518
that we understood the question um we understood the premise can
519
you maybe elaborate a bit uh more on the the question please
520
so yeah my question is are the characteristics the characteristics of the business idea
521
so highly developed versus less developed business idea
522
different from the mechanism you say as you know drivers for the performance outcome you observe
523
So I kind of see a mix between, you know, the characteristic of the business ideas and the mechanisms that connect the,
524
you know, the business ideas to the success, the performance.
525
Okay, so let me elaborate a bit on that, on the answer to this question and Chiara maybe can elaborate
526
and then you will tell us whether it answers or not your question.
527
So essentially our idea is that firms at a different level of business development face different problems.
528
So firms at a lower degree of business development are still validating the value proposition.
529
And this is the first point that you were suggesting.
530
And firms at a later stage are fine -tuning the value proposition.
531
So your question is, we understand that these are the two characteristics.
532
Tell us more about the mechanism.
533
And the idea for us is that for firms that are still developing the value proposition,
534
the method helps them make some higher level decisions, which can be, you know,
535
what is the customer, the target customer that we want to face.
536
So obviously, the method at this stage is relevant.
537
It helps them decide.
538
But this is like one out of several important choices that they're making.
539
So this might lead them to make more investments in a certain customer segment.
540
It might lead them to hire someone who is an expert in that customer segment,
541
but it might not necessarily translate into revenue immediately.
542
But the other thing that we are also thinking about in terms of the mechanism is
543
that this is like a search process in like a broader space, because many there are still many degrees of freedom.
544
So the entrepreneur has to go to I mean, the scientific method works in an iterative way.
545
So obviously each divided theory is further developed over time through these iterations.
546
And so when there are still many high degrees of freedom, first of all, it takes more time to cover the search space.
547
But also each test can be in a way less informative because, or let's put it this way,
548
might be more difficult to run all the like to develop the theory
549
and run all the different tests because if you think about the number of combinations that this entails is actually quite high.
550
On the other hand, if you compare the opposite situation, high degree of business development, very fine -tuned preposition, the search space is much smaller.
551
So the method, in terms of mechanism, to answer your question about the mechanism, can be applied in a much more focused way.
552
And so it quickly serves in providing answers that are like the missing pieces of the puzzle.
553
And then there is a complete picture,
554
which is the finalized fine tuned value proposition which can directly generate revenue.
555
I don't know if Chiara wants to add anything to this.
556
Sure, I think what I'd like to add is
557
that I think Addis went straight to the most difficult part of any field experiment
558
which is you know showing what the mechanism is
559
and obviously as this presentation shows these are preliminary results
560
so this is really the part of this project where ellen
561
and i are spending more time now
562
so really trying to show more clearly what is the journey
563
that these firms are going through
564
so i think as you mentioned the idea with the problems is not not
565
so much to show that they are the mechanism
566
but rather to show that that's the starting condition
567
so these firms actually face different problems which is something
568
that is consistent with the literature but then the mechanism are these different changes
569
that they're making so we're trying to work more on pivot
570
and other intermediate outcomes to show that a little bit more clearly
571
so i think this question is very helpful for us to to really clarify
572
that we need to focus on that a little bit more
573
and i think at this point is also closely related to the question
574
that miriam has that i see in the chat
575
miriam would you like to unmute and ask your question okay now you can hear me right yes Yes,
576
my question is very much related to the previous one and
577
so the first part of my question actually is a comment
578
and it's to make sure that I understood basically the main conclusions of the paper
579
which is one size basically does not fit all.
580
So it depends on the stage of the business cycle of the specific firm, how this firm adopts the scientific method,
581
the cognitive method and it depends on the outcomes that you're looking at.
582
Now, my point here is whether it's about the way the different firms,
583
according to the stage of the business development, use the scientific method that is different,
584
or whether they make different decisions because they are in a different stage of the business cycle,
585
and therefore they have to make decisions that are different compared to firms
586
that are more like ahead in terms of the business development.
587
So if you want, my question is confused because it's not clear to me what somehow what I want to ask,
588
but so whether this is an issue concerning the way firms use the scientific method,
589
whether it's a matter of the decisions that different firms at the different stage have to make.
590
So what comes first here that explains your finding?
591
yeah i think it's a very clear question actually it's not it's not confused at all um
592
so maybe i can start and then uh elena please feel free to add
593
because it's quite a broad question anyway um
594
so i really like how you summarize this idea of one size doesn't fit all
595
which might be one of the key takeaways
596
and i think elaborating on this point what is interesting is
597
that especially for policy makers for accelerators for us as educators
598
this suggests there might be better ways to help these entrepreneurs
599
which are really early in their journey of developing a new business now i think the caveat also
600
that we need to keep in mind when we interpret these results is
601
that the study has a fairly limited duration right
602
so precisely for the reasons
603
that you're discussing about the different type of problems it might be
604
that these early stage entrepreneurs need more time to reach a
605
stage where we can really see the benefits of using a scientific approach
606
and so the fact that they're facing these different problems might imply that they need more time.
607
So hopefully this is something that we will be able to measure later on at some point, as Elena mentioned earlier, with additional data.
608
But I think this is an important caveat and something
609
that we're thinking about in terms of how to interpret the results in a fairly cautious way.
610
But Elena, I'd love to hear your thoughts about this.
611
What comes first, problems, decisions?
612
Absolutely.
613
Thank you, Miriam.
614
It's obviously a very important question, and I particularly think that from a practical standpoint,
615
your suggestion in the chart of looking at intermediate decisions,
616
because I mean, essentially what we are saying here is also that between growing the firm,
617
like defining the value proposition and making revenues and exploiting that value proposition, there's really a lot.
618
And so it would be really nice to be able to map.
619
the data generation process there with possibly looking at intermediate outcomes,
620
so this is in fact why we in the following studies,
621
these are things that hopefully we will have the opportunity to observe so that it will provide additional evidence in this direction.
622
With this specific study, we obviously are limited to what we measured, so we are trying to provide some evidence in that direction,
623
but it's certainly where I mean it's certainly the direction to go in
624
because it's a very important opportunity to map the decision making process
625
and understand more about how I mean about the process
626
that goes from making the decision to observe some intermediate outcome and then investing more until performance is observed.
627
Thank you.
628
Thank you.
629
I think we're coming very close to the end of the session.
630
So I'll leave it to Emily or Ryan to wrap up.
631
But what I want to say for sure is
632
that I would to thank everyone for being with us today and taking the time to attend our presentation
633
and we would really love to to hear any thoughts um any ideas
634
or suggestions so please feel free to reach out to us
635
and we would be delighted to continue this conversation thank you thank you everyone.
✨ วิดีโอแนะนำ
C11
60 ประโยค
Quick Study: How Venture Capitalists Make Decisions
Daily ConversationUniversity StudentsWorking Adults
C11
259 ประโยค
Talk Back: Why Arguing With Yourself Can Help You Flourish
Daily ConversationUniversity StudentsWorking Adults
B21
157 ประโยค
Introduction to Economics Part 2 - Professor Ryan
Daily ConversationUniversity Students
![The Paradox of Choice • Level 4 [B2] • ESL Listening](https://img.youtube.com/vi/4MzrgdfIgi8/mqdefault.jpg)
B26
14 ประโยค
The Paradox of Choice • Level 4 [B2] • ESL Listening
Daily ConversationUniversity StudentsWorking Adults
C11
346 ประโยค
Trust the Process: How to Design Teams That Actually Work
Daily ConversationUniversity StudentsWorking Adults
B21
147 ประโยค
You MUST learn time management as a student.
Daily ConversationHigh School StudentsUniversity Students
C14
263 ประโยค
Improve English with B2–C1 English Shadowing Practice | Advanced Speaking Workout
Business EnglishDaily ConversationUniversity Students
C13
28 ประโยค
Evidence Markets: Upgrading Prediction Markets
IELTS PrepTOEFL PrepUniversity Students
C15
34 ประโยค
Marketing Research Essentials Intro, Models & Intelligence
Business EnglishUniversity Students
![[C1] Stop Overthinking | English Listening & Speaking Practice](https://img.youtube.com/vi/p7oFZJmTjv0/mqdefault.jpg)
C1158
63 ประโยค
[C1] Stop Overthinking | English Listening & Speaking Practice
Business EnglishDaily ConversationUniversity Students
C17
25 ประโยค
Should I Choose Passion or Duty?
British AccentBusiness EnglishDaily ConversationUniversity Students
B22
17 ประโยค
British Council Listening Practice A talk about motivation
Business EnglishDaily ConversationUniversity Students
คำศัพท์และข้อสังเกตด้านการพูดสำหรับบทเรียนนี้
วิดีโอนี้มี 635 ประโยค และ 8602 คำ สำหรับฝึกพูดตาม ช่วงที่มีเสียงพูดยาว 56:26 ผู้พูดพูดด้วยความเร็วเป็นธรรมชาติ ประมาณ 152 คำต่อนาที ใกล้เคียงกับบทสนทนาในชีวิตประจำวัน 86% ของคำอยู่ใน 3,000 คำที่ใช้บ่อยที่สุดในภาษาอังกฤษ ส่วนที่เหลือควรดูไว้ก่อนเริ่มฝึก
คำศัพท์สำคัญในวิดีโอนี้
คำที่ควรเรียนรู้ 15 คำจากวิดีโอ พร้อมคำอ่านและความหมาย:
| คำศัพท์ | คำอ่าน | ความหมาย |
|---|---|---|
| entrepreneur คำนาม | /ˌɑn.tɹə.pɹəˈnɝ/ | ผู้ประกอบการ |
| proposition คำนาม | /ˌpɹɑpəˈzɪʃən/ | ประพจน์ |
| mechanism คำนาม | /ˈmɛk.ə.nɪ.zəm/ | กลไก, เครื่อง |
| observe คำกริยา | /əbˈzɜːv/ | สังเกต |
| canvas คำนาม | /ˈkæn.vəs/ | ผ้าใบ |
| uncertainty คำนาม | /ʌnˈsɜːtənti/ | ความไม่แน่นอน |
| hypothesis คำนาม | /haɪˈpɒθɪsɪs/ | สมมุติฐาน |
| tune คำนาม | /tjuːn/ | ทำนอง |
| necessarily คำกริยาวิเศษณ์ | /ˌnɛs.əˈsɛɹ.ə.li/ | ต้อง |
| extent คำนาม | /ɪkˈstɛnt/ | ขอบข่าย, ขนาด |
| experiment คำนาม | /ɪkˈspɛɹ.ə.mənt/ | การทดลอง |
| slide คำนาม | /ˈslaɪ̯d/ | กระดานลื่น |
| imply คำกริยา | /ɪmˈplaɪ/ | หมายความ |
| interpret คำกริยา | /ɪnˈtɜː.pɹɪt/ | ตีความ |
| explanation คำนาม | /ˌɛkspləˈneɪʃən/ | การอธิบาย |
การออกเสียงที่ควรระวัง
ผู้พูดใช้รูปย่อและรูปลดเสียง 55 ครั้ง เช่น they're, we're, don't ให้พูดแบบสั้นตามที่ได้ยิน
- เสียง “th”: hypothesis /haɪˈpɒθɪsɪs/, gather /ˈɡæðɚ/
- เสียง “sh” และ “zh”: proposition /ˌpɹɑpəˈzɪʃən/, essentially /ɪˈsɛnʃəli/, explanation /ˌɛkspləˈneɪʃən/, presentation /ˌpɹɛzn̩ˈteɪʃn̩/, beneficial /ˌbɛn.ɪˈfɪʃ.əl/
- คำยาว — ลงเสียงหนักให้ถูกพยางค์: entrepreneur /ˌɑn.tɹə.pɹəˈnɝ/, proposition /ˌpɹɑpəˈzɪʃən/, mechanism /ˈmɛk.ə.nɪ.zəm/, essentially /ɪˈsɛnʃəli/, uncertainty /ʌnˈsɜːtənti/
วิธีฝึกกับวิดีโอนี้
- ฟังวิดีโอให้จบหนึ่งรอบโดยยังไม่ต้องพูด แล้วจดคำที่ยังไม่รู้จัก
- เริ่มที่ความเร็ว 0.75× พูดตามทีละประโยค แล้วกลับไปใช้ความเร็วปกติเมื่อเริ่มคล่อง
- อัดเสียงตัวเองแล้วเทียบกับต้นฉบับ โดยสังเกตคำอย่าง entrepreneur, proposition, mechanism เป็นพิเศษ
ไวยากรณ์ในวิดีโอนี้
โครงสร้างที่ผู้พูดใช้บ่อยที่สุด พร้อมคำพูดจริงจากวิดีโอ:
| โครงสร้าง | ในวิดีโอ |
|---|---|
| Present perfect have/has + กริยาช่อง 3 — เหตุการณ์ในอดีตที่ยังเกี่ยวข้องกับปัจจุบัน | have been identified · has suggested · has identified |
| Passive voice be + กริยาช่อง 3 — เน้นสิ่งที่เกิดขึ้น ไม่ใช่ผู้กระทำ | are characterized · have been identified · could be met |
| Relative clauses who / which + อนุประโยค — ข้อมูลเพิ่มเติมเกี่ยวกับคนหรือสิ่งของ | one who starts · one who draws · someone who tests |
เทคนิค Shadowing คืออะไร?
Shadowing เป็นเทคนิคการเรียนรู้ภาษาที่ได้รับการรับรองทางวิทยาศาสตร์ พัฒนาขึ้นสำหรับการฝึกนักแปลมืออาชีพ วิธีการนี้เรียบง่ายแต่ทรงพลัง: คุณฟังเสียงภาษาอังกฤษจากเจ้าของภาษาและพูดตามทันที — เหมือนเงาที่ตามผู้พูดด้วยช่วงเวลาห่าง 1-2 วินาที การวิจัยแสดงว่าเทคนิคนี้ปรับปรุงความแม่นยำในการออกเสียง ทำนองเสียง จังหวะ การเชื่อมเสียง การฟังเข้าใจ และความคล่องแคล่วในการพูดได้อย่างมีนัยสำคัญ