Explain and predict and make your own hammers

Today's writing is only in English. Sorry Finnish readers, I am short on time. Today I am in Turku School of Economics, sitting in a lecture with PhD students.
First of all, yesterday is somewhat of an identity crisis for me. I am no longer a PhD student. This role has been with me for such a long time. It has been quite comforting label, I am just a PhD student - I am still learning. Is there something scary of saying ‘Post doc’? It suggests that I now know something about the world, right?  It was something I thought about yesterday. If I am no longer a PhD Student, can I still turn up in jeans and a t-shirt? Or should I be wearing black pencil skirts? Obviously there was no point in my Monday morning contemplation. Perhaps it was a residue of social norms imposed on me by my upbringing or what I think the society would like me to do. That is however not how I want to live my life, my life should be a collection of my own choices, not someone else's. I should do what makes me feel good. So I wore a pair of jeans and House t-shirt. Because that’s what I was feeling like.

But this seminar is about Theorizing and I am still talking about clothes. Surely that makes me rather superficial...? Or is it, that I am trying to understand my own behavior or thinking process?

So today I am in Theorizing in Information Systems Science Course by Anol Bhattacherjee. Now, those of you who have been reading my blog for a while, know, that I attended a very similar course a few years back and I wrote about that course here and here.


So why do the 'same' course twice? Well one answer could be that, Prof. Bhattacherjee is one of the legends of our field, which obviously makes it worth my while to travel to Turku for two days to hear what he has got to say in this area. But mainly my reasoning was: Making theories is not easy. It is always a good idea to learn more about it. So I came to this event based on a) reputation of the lecturer b) the high interest towards the topic and c) lifelong learning perspective.

  Prof. Bhattacherjee started his course by talking of stories and claiming that theories are stories with academic evidence behind them. I liked this approach quite a lot. The symbolism worked for me. I am still looking for that topic for the next big stream of study. Yes I am very bored with my PhD topic and now it is time to do something else. I am looking for the characters and the plot that would be interesting enough. If the characters are all boring, it's probably not a story worth telling. What I need is to find constructs (characters) which would be interesting enough for me as well as for the world, to create a story (a theory). So spot on this seminar gave me a way of re-thinking what I was doing and motivating me into starting to theorize.

INFORTE events are often interesting melting pots of many cultures coming together. That brings extreme richness to the discussions during the seminar days. These two days was not an exception. In this case, there was the American lecturer meeting a 'Finnish PhD students' international audience. In the start of the first day, everyone is still a little lost. The audience is trying to reflect on what the lecturer says. Bhattacherjee is a rather approachable, playful, humoristic and specifically sarcastic lecturer. Using humor and sarcasm with a Finnish audience is always a learning curve for the American lecturers. Finns need to warm up to get the cues and not everyone, (even after two days of being stuck in a hot lecture room together with the speaker) will know when he's serious and when he is sarcastic. My experience of this seminar was that on the second day, the audience had learned to know the style of the lecturer and therefore the second day was the gold mine of this seminar.  

University of Jyväskylä had sent quite a delegation to the seminar - perhaps even 50% of the students came from our university. Perhaps the reason for that was encouragement towards theorizing in our university. The strategy of Computer Science and Information Systems department currently underlines publishing in Top IS journals and that is a lot more likely to happen for researchers who know how to theorize.  

JYU Crew potrayed by (c) Juuli Lintula

What is a Theory?

"Analytic structure of system that attempts to explain a particular set of empirical phenomena." (Saphira, 2011)

"A system of constructs and propositions that collectively presents a logical, systematic and coherent explanation of a phenomenon of interest within some assumptions and boundary conditions."(Bacharach, 1989)

A Theory...
a) Describes what is happening
b) Explains why it’s happening
c) Predicts what might happen

 Spring was certainly happening in Turku this week.

 On day one, we talked about types of theories. What is a variance theory, process theory, grand theory, middle-range theory, meta theory... And obviously the discussion did not end when the lesson hours ended at 4:30pm.

 On day one, Bhattacherjee also talked about Building blocks of Theory:

• The Constructs
• The Propositions
• The Logic
• The Assumptions/boundary conditions

 Obviously we were also talking what theory is not. Is model a theory? Is model a representation of a theory? Is TAM a Theory? These are questions which it does not really matter how many seminars you attend, are still relevant, are still discussed, you can always comment on. Bhattacherjee has opinions, but he is also very humble in presenting his knowledge - sometimes these are matters of language and semantics. Sometimes supposed "new theories" are old theories in new bottles. Perhaps there are NO theories in IS... That's certainly being proposed. That there is no such things as native IS theories - all theories are just theories adapted from psychology, management, marketing or some other older and more established area of science.

 On Day one we were also discussing what is a typology and what is a taxonomy. Labels might be just those names that scientists gave certain frameworks or phenomenon. Does not mean they are always correct, accurate or good representations of what information the scientist was trying to share with others. Does not mean that we shouldn't pay attention to the labels. Science is about discourse. It is important to at least try to give things names so that other people could somehow understand what we are trying to say. Is there any point in a theory if you never share it with anyone? Sure, you can use it in your own life from now on. But it is not science, if we don't bring our theories to the community to discuss, to falsify, to argue, to agree with. Day one was helpful on going through the meaningful labels around theorizing.

 As we looked at our reading list even before the course, we could observe that Bhattacherjee has a different perspective from the norm of theorizing to some extent. It took the room 3 hours to get to the obvious question: Where is Shirley Gregor's (2006) paper... The bold answer of professor Bhattacherjee was that he never understood the paper. Perhaps we use some papers as the 'de facto'... This was a good reminder that we should constantly question the 'hammers' that we are given. 

 Day two was all about discussing how to do theorizing. Should I do deductive or inductive... How to find constructs. How to find plots and so on. What I learned was, that it does not matter which one you start with. To do real research, theorizing, you should do both. Perhaps you are better at the deductive part. Perhaps you are better at the inductive part. Does not matter. You should be able to do both.

What I also found out, was that there is not ONE FIT into your problem. You can use multiple methods. You can do constructs for example by
- Deducting from prior research (Literature review)
- Inductively from empirical evidence, for example by using focus groups, using expert panels, interviews, observations, collecting other kinds of data...
But, of course the research setting should be systematic and it should be fitting to your research question.

 The inductive-deductive discourse was still continuing after hours in the lobby of Hamburger Börs, where tensions were starting to build on whether we had understood what the professor was saying, correctly.
The night in Turku was rather warm and beautiful. 

 I guess many of the things discussed in this seminar, were familiar to me. However, what one cannot undermine is the psychological effects of listening to one of the top of the field talking to you. First of all,
1. You always learn a lot of new things.
2. You get new ideas and fall into deep discussions with your peers who have even more great and smarter ideas, over a bottle of wine. And isn't that what life is all about? Good conversation.
3. You get new fresh energy and enthusiasm to continue one's research - with this momentum, papers are written and theories are born.

 Personally, it was a relief to learn that one should start data collection and memoing any time. Or that you could start analyzing your data any time. Often I have felt like I have to do things in certain order, which has been stopping me from making observations, coming up with ideas, analyzing data, starting to do things. I now understand that I have to make my own way. And it is okay to do it my way. Of course I can copy hammers that others in the field have proposed. Probably they are good, someone has tested them, someone has used them before - or at least thought of them. But my experience as a creative scientist sometimes can lead me into other ways of collecting data or moving ahead. I should not be so restricted by the fences that previous researchers on my field have been doing. It does not mean that I shouldn't do it well, water tight or logically. But it is deliberating to me to think, I can make my own hammers.

It hopefully is clear to you, that I immensely enjoyed these two days of thinking, learning and discourse. I sure am one of the lucky ones in order to be right here in my life, in this particular generous science community, having absolute freedom to do what I want as my job. Thank you professor Bhattacherjee for sharing your stories with us.

"It does not matter what method you use. 

What matters is that do you have a theory at the end." 

(Bhattacherjee, 2016)

Does this sound like anyone we know in the field?

Ideas into Theories

Today I will make an exception and write my blog in English only. It's because I work in academia in English only, so anyone who is into this stuff is going to be able to read it in English, turning it into Finnish would have some value, but I am not a translator, I'm a scholar, so today this should pass in lack of time. Please excuse me, Finnish readers.

There was no lecture diary in this course 'Developing Theories in IS Discipline?' (First day I reflected on this post) Regardless I wanted to reflect on what I learned in the last two days of the course. For myself as well as probably for others who would have wanted to be there, but couldn't because of conferences etc. Firstly I would say, the topic of developing theories is not an easy one. I would say it's about as hard has it gets for a researcher. And if you can do it well, you can not only pay the bills for the rest of your life, but also make you 'a star' in your field, bringing lots of positive attention towards you. So those are two really good reasons to come up with your own theory. The work is hard, but the rewards are grand. 

On this course, in 1,5 days, we tackled the topic of Theory Creation in an agile way - the reading list was looong (28 papers) and we also fitted a two part practical theory creation session/exercise. I could have spent a whole week on this topic and I would have extended the practical parts saying: now take this hammer, and look at your theory from this perspective, now take this hammer and look at it from another etc. The hammers being the classic papers for evaluation, which we did cover. But there is also a different value in doing this kind of course in a fast-lane. It means that people can fit it to their schedules. It makes people really focus, which might not be the case for 5-day-courses. 

Regardless, I have learned immensely this week. Not only about theory creation, but about our discipline, Information Systems has been evolving over time and of course the kind of competences which I should have being a researcher in this field. So I thought I'd share some of the reflections which I have been discovering:

 

IS as Discipline

Firstly Information Systems (IS) as a field, is not quite computer science (which my Master's degree is on) and not quite social sciences, but something in between. Often IS studies have been described to have two dimensions: The technical and the social. So we are not just interested in how the technology works, but also how humans interact with it, use it. The field has had to defend its existence, being quite a young discipline, for example by defending the fact whether we have got native theories which are specific just for us. Two theories most known (and used) on this field are:

• Technology Acceptance Model (TAM) (Davis et al, 1989; Venkatesh et al., 2003)
• Delone & McLean IS Success Model (Delone & McLean 1992, 2002, 2003)

However it has been argued that particularly TAM is utilizing meta theories from other disciplines (such as the Theory of Planned Behavior and the Theory of Reasoned Action) which would point towards IS not having native theories. However, there are constructs in both theories very specific just for IS, which in the discourse is the counter argument - so I guess based on this what I learned was that one of the most crucial parts of theory creation is the question: How far you need to go from the original/meta theory(ies) behind your own... Make sure it's far enough. However, the world is evolving and many of the theories used in let's say, disciplines which claim to be well established like management or economics, have taken parts of theories from 'older' fields such as psychology or history. So the key competence here is to understand, what is specific for our field and why the meta theories on their own just don't work.

These two theories are not by far the only native theories we have... I guess this week I've learned something about the pride of belonging to the IS research field. Those wanting to reflect on this, I would suggest to read Straub's 2012 Editorial on Does MIS have Native Theories? in MISQ.

How to build the theories in practice?

In the course we looked at many possibilities on how to do it. Many methods, many criteria, many checklists, many hammers. You can choose various starting points for theory creation and you can proceed with many methods, there is not just one tunnel, which of course is the challenge. In the practical workshop my group proceeded like this:

1. We tried to narrow the problem and decide on the research question, also trying to think what would be interesting. However, we had 45 minutes for this exercise, which meant that we didn't really have time to reflect too much on our decisions. Luckily I was working with very competent and resourceful people, so we advanced quite quickly...

RESULT: Research question: "What factors predict dissertation acceptance in 4 years?"

2. Secondly we decided to take an inductive approach and did a quick interview round on what each of us thought were the keys for their success in our phd studies. Based on this 'grounded theory' style approach, some constructs were immediately rising and we were grouping them and thinking on what could effect what (what would our hypothesizes be).

RESULT: Constructs like "Data Access", "Topic Choise", "Researcher's characteristics", and "Formal support available"

3. We contemplated the issue of whether to do a process model or a variance model. But ended up deciding on the latter, as it was time management vise more feasible. What is the difference between these two approaches? The main difference is that process model has a sequence, a timeline of some sort. So then we drew a very simplified model presentation of our theory, where these constructs would be affecting the doctoral study success.

RESULT:  Theorethical framework

 (c) Clements, Heiskala, Nykänen, Pirhonen, Salminen & Tiilikainen

4. Then we started thinking of theoretical backgrounds for each construct, the measurability and practice. We were just about to reflect on related theories in related disciplines when we ran out time. The next steps should have been to go to literature and look for solid reasoning for each constructs and then of course testing the correlations, looking for causality. 

RESULT: Some justification for our model  

On the second day, we presented and gave feedback also to our peers. Learning from the others' thinking process was for me the biggest lesson of this part. It's fascinating to listen to peers who have had slightly different background. I also learned a lot more about reviewing, how to give critique with various styles. I would say that based on the characteristics of different scholars, they have different strong-points. In a seminar like this, one can identify 'what might mine be' and 'how I can contribute to a peer-relationship/joined paper writing'?

Hammers and Building Blocks

Another level of this course was the reading. We all needed to do 2 summaries, one powerpoint and also contribute into a few more papers discussion. So overall, I'm sure all read at least 5-6 papers of the 28 very intensively and browsed through the others. I am calling these papers the hammers and the building blocks. These terms point to the review process: If you are the reviewer of a theory paper, you might use Weber 2012 as your hammer. If you are the author, you might use Gregor 2006 to defend your approach when reviewers' ask for revisions.

One list, which I would like to raise is from a very recent editorial of MISQ by Rivard (2014): 

Checklist for theory creation

1. Motivation
2. Definition 
3. Erudition
4. Imagination
5. Explanation
6. Presentation
7. Cohesion
8. Contribution

Based on this and reflecting what I learned this week, I made my own list..

Kati's 10-points check-list of theory creation learned on this course:

1. Tension/Motivation - what is it? Why this problem? It's not enough to say "no one has done it, so I'm doing it." That's not good enough. Why is this INTERESTING? Are you trying to explain and/or predict? Before you even begin, read Gregor 2006 at least three times. Reflect on the type of theory you would like to invent.

2. Take a particular perspective, reflect on whether it is too broad, again, is it interesting enough? Narrow down. If you are doing IS theory - what's the topic's relationship to IS? 

3. What is already known of this topic? Do your reading.

4. Select your research approach: After which take 20 papers that use the same approach as you, study them and then write your paper - learn by examples

Specifically I would like to mention that the tactics on doing 'Grounded theory method -> Process theory' is at least something to look at. I understand that this is not a method for all, but if you know how to do it well, it could be a winner. Personally for me, the peer and supervisor support in my department exists for this, so I'll definitely look into it.  Both Sarker and Siponen have widely used this approach, if you want to look at some of their papers as examples.

5. Select your constructs well (why this one, why not another?) Have the 'wow' factor - why is this interesting? What is new? Are they coming from the data? Are they coming from literature?

6. Answer the question: What is your meta theory? Look at related theories so you can explain why not this one, why this one

7. Define your constructs very clearly! Discuss your boundaries!

8. Is it variance or is it process? if latter, also think of the sequence
Later in the course we had a small reflection on the paradox - are these two completely different after all...

9. Label your theory well - Have some sex appeal! Style is important, but if you are using dramatic words, then you also need to deliver. Marketing itself is not enough, there needs to be the substance to back it up. I have colleagues who feel that the conservative approach is much safer route to publishing success, but personally I find this approach just as acceptable as long as you argument well. And well, I guess I'd rather jump than to play it safe - that's just a personality issue. I guess the question becomes: If you did solid work and no one ever read it - are you successful? I think science is a community for discourse and we can only evolve through the feedback that we get from others. This is my argument for creating something that sticks out rather something that makes people fall asleep. Labels do matter and readers do matter. Part of making science is to make your contribution fit the body of existing knowledge and to be continued through someone else's work in the future. For this, I feel that scientist's moral obligation is to share and market one's own work. It's not enough that you know that you've done it. And in this game, labels do matter.

10. And finally: Read like Crazy:  (at least these on top of your topic literature, and this would be my suggestion of order based on this course)

1. Gregor 2006 (Nature of Theory) Absolute must.

2. Rivard 2014 (Ions of Theory Constuction)

3. Weber 2012 (Evaluating and Developing Theories in the IS Discipline)

4. Sutton & Staw 1995 (What theory is not?)

5. Weick 1995 (What theory is not, theorizing is)

6. Bacharach 1989 (Organizational theories: Some criteria for evaluation)

7. Smith & Hitt 2005 (Learning how to develop theories from the masters)

If you are doing case study: 

- Eisenhardt & Graebner 2007 (Theory Building from Cases: Opportunities and Challenges)

if you are doing design science:

- Gregor & Jones 2007 (Anatomy of a Design Theory)

if you are doing a process model:

- Sarker & Sahay 2003 (Understanding Virtual Team Development: An Interpretive study)

- Pentland 1999 (Building Process Theory with Narrative: From description to explanation)

And finally I would read:
Van Maanen 1995 (Style as Theory) - which might have become the paper which had the most effect on me in these two days. I don't know if Sarker assigned this paper to me on purpose or not, but in any case, I am glad he did. It's an extremely abstract, philosophical and difficult paper, but what it does is amazing. It says: We should be able to break the rules in order to be able to look at things from new - outside the box perspectives; as long as we can still communicate with the science community, it's the right way.

Personal researcher's confidence

Finally, I can say that I learned about myself as a researcher. One could say that I have a bad self-esteem as a researcher. Often I feel like I don't have what it takes. Not after these days though.  That's what I bring home from the course, maybe more valuable than any reading list.

And even with the fear of embarrassing our wonderful lecturer, I just can't shut up on how much effect his courses over the years have had on my personal researcher competence development. I'm sorry - part of being a Finn is to say things straight up. And the great thing about Finns is that if a Finn says something, they mean what they say. You don't have to wonder if it's true or not. Looking at the faces on this course, discussing the issues with my peers, I know that I am not alone with this kind of feedback.  

What Sarker does is gives you confidence, to take the next steps. He works through the researcher's identity, which is extremely personal and motivating. He talks of his own struggles. He talks of his own identity development. I looked at him going through the room of 30 students in breaks, many of which had just come to hear him speak, actually remembering names of people who he has met *once* before two years ago...

It's the little things like he'll say to you "Do you remember..." but then stops himself to say "of course you don't", to make sure that the researcher in question does not feel embarrassed, but empowered. He will carry everyone in the class on the levels that they need, and that I think that is exceptional. He doesn't only give good feedback, but has a kind of Socrates style approach of allowing you to come up with the ideas yourself by assisting the thought process. This way the student will feel a much deeper connection to the ideas and is much more likely to be able to utilize them in the future. Purely looking at the way he gives guidance and support, one can learn so so much. I admit, I might be a little bit excited (not in a creepy way) about Sarker. And yes, it's also true that some styles appeal to some people more than others. I can say that Sarker's style is clearly my cup of tea. How often do you have 2 hours available right next to Kamppi and you choose to do *homework* instead of going shopping... Just a question.

And finally Henri, you are right - this is my subjective, not objective opinion. But what's wrong with looking at research / pedagogical styles in a personal level? It doesn't make it any less valuable, on the contrary, it might have much deeper effects on one's identity development.

And Finally2(I know this is wayy too long summary): If you made it through this whole essay - congratulate yourself! For phd students, If you haven't yet gone to hear Suprateek Sarker speak, there's opportunities available almost every year in Finland, as he's a visiting professor in Aalto University, make sure you won't miss them. You won't regret it. In Finland, we are incredibly lucky. We've got all these high quality speakers visiting us. In my own department I also feel I am lucky, because there's great opportunities to get feedback from world class scholars as well as a great group of peers. I feel very privileged. If you are a PhD student lost in your own topic, feeling lonely and lacking confidence - look around you. There's great support available closer than you think. 

Thank you for Professor Sarker for his wonderful lecture, thank you all the peers for the lively discussions and specifically for my group - I would do theory with you guys anytime!

Tutkijan vaikein kompetenssi - Teorian tekeminen?

Niin kuin mainitsinkin, tällä viikolla olen ollut opiskelemassa teorioiden tekemistä Inforten 'Designing Theories in IS Dicipline', jota vetää Suprateek Sarker. / As I mentioned before, this week, I'm in Helsinki, learning how to make theories in a course called "'Designing Theories in IS Dicipline'"

Olen aiemmin osallistunut Sarkerin kursseille Helsingissä ja Jyväskylässä. Molemmilla kerroilla olin niin inspiroitunut ja sain niin paljon, että tietysti halusin lähteä myös tälle kurssille. Voisipa sanoa, että olen varsinainen Sarker-groopie. Se johtuu siitä, että hän mielestäni osaa todella erinomaisesti päästä nuoren tutkijan tasolle nöyrällä ja kiinnostuneella asenteella. Ei tietoakaan ns. ison staran egosta, joka monella muulla saattaa olla noussut hattuun. Hän antaa avoimesti palautetta ja hän jakaa viisauttaan ämpärikaupalla. Esimerkiksi tämän viikon kurssejen anti on sanoisin sama kun kahlaisin kuukausia itse kirjallisuutta aiheesta "Miten teen teorian/puolustan omaa näkemystäni kun aikakausilehden toimittaja sanoo, että sori sulla ei oo tarpeeksi kontribuutiota tässä". Siis kaksi päivää ihan puhdasta kultaa tämä. / I have previously attended Sarker's courses in Helsinki and Jyväskylä and on both times I was so inspired afterwards that I changed the way I do research. So of course I wanted to come to this course as well. One could say that I'm a Sarker groopie. It's because he does what he does extremely smart: He can coach young researchers with an interested attitude and humble mind, which shows no signs of a 'big star syndrome', even though he's one of the legends of my research field. He knows how to give feedback, how to constructively guide you and he'll even hit you to the head with a bucket of wisdom. For example this week's reading list equals months of my own work just to identify which papers should I take into consideration when I get critism from a journal editor saying 'your paper lacks contribution'. The list of weapons (28 articles(!)) is very comprehensive and even though the paste of this course is faster than lightning, I will claim that I learned more than in months of going through references on my own. Two days of pure gold.

 Tähän kurssiin oli integroituna myös käytännön jakso, jossa ryhmätyönä kehitimme uutta teoriaa, jonka piti olla väikkäriopiskelun ympärille rakentuva. Meidän teoriamme 'Theory of Doctoral Students Success' oli laaja kuin pullataikina ja otti lyhyiden haastattelujen jälkeen konstrukteikseen mm. Tukitoimet, sosiaaliset suhteet, yksilön luonteenpiirteet ja väitöksen aiheen... / There was a practical part of this course, which included a group work of creating a theory around Doctoral studies. Ours was 'Theory of Doctoral Students Success' and it was a very broad theory, including the constructs of personal characteristics of the researcher, social relationships, topic of the dissertation, access to data etc.

Tämä harjoitus oli hyödyllinen ja sen sisällä oli kiinnostava seurata eri tutkijoiden erilaisia ajatusprosesseja. Itselläni on edelleen hakusessa kaksi perustavanlaatuista asiaa, joihin toivon kakkospäivän tuovan valoa:

1) Mikä on tarpeeksi hyvä selitys jollekin konstuktille? 

2) Mikä on tarpeeksi kiinnostava 'uusi ajatus' se 'wow'? Eli jos aihe on liian lattea niin se tuskin pääsee julkaisuun asti.

Nämä lienevät ne keskeisimmät ongelmat minun tutkijan kompetensseissani. En ole varma, ovatko abduktioni oikeutettuja - teorian on noustava datasta, mutta se ei ole pelkästään dataa vaan siinä on myös mukana sitä jotain tutkijalta itseltään. Vaikka itse tiedänkin pystyväni ns. Outsidethebox ajatteluun, en ole varma, miten kaukana boksista voin liikkua ja mitkä ovat säännöt. Siihen taas auttaa näiden 28 paperin lukeminen. "Read like mad and then discuss", siinäpä oiva lausahdus tältä päivältä. Ehkäpä itse tykkään Sarkerista tutkijaesikuvana juuri siksi, että häneltä löytyy sellaista draivia ja passionia, jolla myös itse maailmaa jäsennän. Koska ihan oikeasti - mitä järkeä on tehdä jotain sellaista, jota ei rakasta?

This excersise was very useful as it allowed me to observe the thinking process of other researchers. I personally feel I lack two very important research competences which I hope this course brings in insights on the second day:

1) What is good enough explanation/justification for a construct?

2) Which ideas are exciting enough? If the dissertation's 'new' thing is 'you should have more coffee breaks' then one should argue that we already knew that - how to make some new and exciting thoughts into the world?

I suppose these are the most crucial issues in researcher's competence development. I am not sure if the abductions that I make are justified, theory must be rising from the data, but it should not be 'just' data... It should integrate some ideas from the researcher him/herself. Although I know I am well capable in 'outsidethebox' thinking, I am not sure how far from the box can I go and what are the rules. That's exactly what the 28 articles are there for to read. Perhaps I like Sarker as a rolemodel because he has that drive and passion which I attack the world with. Because to be honest, what's the point in doing something that you don't love?