Dec 30, 2016 - International Journal of Agile and Extreme Software Development 1(1): 78â94. IV Sarja J, Saukkonen S (2016) Developing technology pushed ...
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UN NIIVVEERRSSIITTAT ATIISS O OU ULLU UEEN NSSIISS U
Jari Sarja
University Lecturer Santeri Palviainen
Postdoctoral research fellow Sanna Taskila
Jari Sarja
Professor Esa Hohtola
DEVELOPING TECHNOLOGY PUSHED BREAKTHROUGHS DEFINING AND ASSESSING SUCCESS FACTORS IN ICT INDUSTRY
Professor Olli Vuolteenaho
University Lecturer Veli-Matti Ulvinen
Director Sinikka Eskelinen
Professor Jari Juga
University Lecturer Anu Soikkeli
Professor Olli Vuolteenaho
Publications Editor Kirsti Nurkkala ISBN 978-952-62-1446-7 (Paperback) ISBN 978-952-62-1447-4 (PDF) ISSN 0355-3191 (Print) ISSN 1796-220X (Online)
UNIVERSITY OF OULU GRADUATE SCHOOL; UNIVERSITY OF OULU, FACULTY OF INFORMATION TECHNOLOGY AND ELECTRICAL ENGINEERING
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SCIENTIAE RERUM RERUM SCIENTIAE NATURALIUM NATURALIUM
ACTA UNIVERSITATIS OULUENSIS
A Scientiae Rerum Naturalium 685
JARI SARJA
DEVELOPING TECHNOLOGY PUSHED BREAKTHROUGHS Defining and assessing success factors in ICT industry
Academic dissertation to be presented with the assent of the Doctoral Training Committee of Technology and Natural Sciences of the University of Oulu for public defence in Auditorium IT116, Linnanmaa, on 30 December 2016, at 12 noon
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Copyright © 2016 Acta Univ. Oul. A 685, 2016
Supervised by Professor Samuli Saukkonen
Reviewed by Professor Joakim Wincent Professor Saku Mäkinen
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ISBN 978-952-62-1446-7 (Paperback) ISBN 978-952-62-1447-4 (PDF) ISSN 0355-3191 (Printed) ISSN 1796-220X (Online)
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JUVENES PRINT TAMPERE 2016
Sarja, Jari, Developing technology pushed breakthroughs. Defining and assessing success factors in ICT industry University of Oulu Graduate School; University of Oulu, Faculty of Information Technology and Electrical Engineering Acta Univ. Oul. A 685, 2016 University of Oulu, P.O. Box 8000, FI-90014 University of Oulu, Finland
Abstract The main task for most development-intensive organisations is to create, develop and commercialise new products and services. The technology push (TP) concept is considered an important competitive advantage for companies trying to create breakthrough products. Because development processes are risky and failure rates are high, especially in the case of technology pushed projects, defined success factors are valuable knowledge for the management of development-intensive firms. The prime objective of this study is to present a compact set of TP project success factors in an information and communication technology (ICT) context. Because the literature on new product development and innovation has presented many success factors for developed products, but has done so in a way that presents the factors as having a nebulous nature, the specification of TP success factors is also presented. The success factors are also empirically validated. The goal of the validation was to determine the relevance of the success factors introduced, and potentially define new ones. The validation was performed through an empirical study with semi-structured company interviews. As a result of this study we concluded that one success factor defined through the literature review should be removed due to a lack of relevance, that the other twelve success factors were validated, and three new success factors were identified during the empirical study. Eventually fifteen TP success factors are defined and presented. The practical relevance of this study is to help firm management to recognise the real actions needed to reduce product development risks. The theoretical relevance is in helping scholars to focus on key issues when studying the key factors of breakthrough development cases.
Keywords: ICT, new product development, radical innovation, success factor, technology push
Sarja, Jari, Teknologiatyöntöisten läpimurtotuotteiden kehittäminen. Menestystekijöiden määrittely ja arvioiminen ICT toimialalla Oulun yliopiston tutkijakoulu; University of Oulu, Tieto- ja sähkötekniikan tiedekunta Acta Univ. Oul. A 685, 2016 Oulun yliopisto, PL 8000, 90014 Oulun yliopisto
Tiivistelmä Tuotekehitystä harjoittavien yritysten päätehtävänä on luoda, kehittää ja kaupallistaa uusia tuotteita ja palveluita. Yritysten pyrkiessä luomaan läpimurtotuotteita, ”Technology push” -konseptia pidetään niille tärkeänä kilpailuetuna. Koska tuotekehitysprosessit ovat riskialttiita ja epäonnistumisen mahdollisuudet suuret erityisesti teknologiatyöntöisillä projekteilla, tarkasti määritellyt menestystekijät ovat arvokasta tietoa yritysten johdolle. Tämän työn päätarkoituksena on esitellä yhtenäinen ja tiivis joukko teknologiatyöntöisten projektien menestystekijöitä ICT toimialalla. Uusien tuotteiden kehittämistä ja innovaatioita käsittelevä lähdekirjallisuus esittelee lukuisia menestystekijöitä. Ne on kuitenkin esitelty vaikeasti selitettävällä tai monimerkityksellisellä tavalla, joten olemme esittäneet myös niiden tarkat määrittelyt. Menestystekijät ovat validoitu myös empiirisesti. Validoinnin tarkoituksena oli löytää esiteltyjen menestystekijöiden relevanssi ja löytää mahdollisesti uusia menestystekijöitä. Validointi toteutettiin puolistrukturoiduilla yrityshaastatteluilla. Työn tuloksena esitetään kirjallisuuskatsauksen ja empiirisen validoinnin avulla määritellyt 15 teknologiatyöntöisten projektien menestystekijää. Tutkimuksen käytännöllinen merkitys on auttaa yritysjohtoa tunnistamaan tärkeät toiminnot tuotekehitysriskien madaltamiseksi. Tutkimuksen teoreettinen merkitys on auttaa tutkijoita keskittymään avainasioihin ja tunnistamaan menestystekijät läpimurtotuotetutkimuksessa.
Asiasanat: menestystekijä, radikaali innovaatio, teknologian työntövoima, tieto- ja viestintäteknologia, uusien tuotteiden kehittäminen
To my kids
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Acknowledgements I present my warmest thanks to my supervisor professor Samuli Saukkonen for the great guidance I have received during my postgraduate studies. I appreciate the way of discussion, the feedback given and mutual respect shown. I also want to thank my personal academic mentors, Professor Veikko Seppänen and docent Petri Ahokangas for the time, support and encouragement they have given to me. I want to thank the Ahti Pekkala Foundation, the Riitta and Jorma J. Takanen Foundation, and the University of Oulu Scholarship Foundation for financial support for this project. I also want to thank the University of Oulu Graduate School for the travel grants that for one’s part enabled me to study part of the postgraduate courses abroad. I also want to thank the Finnish Literature Society for use of the Tartu Researcher Residence for the editing and writing work. Moreover, I would like to thank the industrial representatives who participated in this study: Asmo Saloranta, Jaakko Olkkonen, Petri Soronen, Niko Lehtonen, Tapio Koivukangas, Janne Pihlajamäki, Pertti Seppänen, Lennu Keinänen and Ilkka Toivonen. I am glad for the understanding of the importance of my research topic not only to the new product development industry in general, but also for regional innovation schemes. Independent financial support is extremely important for individual research outside research groups and has helped me to stay on schedule. Tartu, March 2016
Jari Sarja
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List of abbreviations B2B B2C CEO CTO GPT HW ICT MP NPD R&D SW TP
Business to Business Business to Consumer Chief Executive Officer Chief Technology Officer General Purpose Technology Hardware Information and Communications Technologies Market Pull New Product Development Research and Development Software Technology Push
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List of original publications This thesis is based on the following publications, which are referred throughout the text by their Roman numerals: I
Sarja J (2015) Key factors of successful technology push projects in the ICT context: a review of the literature. International Journal of Information Technology and Management 14(4): 253–273. II Sarja J (2015) Explanatory definitions of the technology push success factors. Journal of Technology Management & Innovation 10(1): 204–214. III Sarja J (2012) A review of the Getting Real software development approach. International Journal of Agile and Extreme Software Development 1(1): 78–94. IV Sarja J, Saukkonen S (2016) Developing technology pushed breakthrough: an empirical study. Journal of Innovation Management. Submitted manuscript.
The first author was responsible for planning the study, collecting and analysing the data, and writing the paper. The second author provided comments about the manuscript and supported the research process with guidance and feedback.
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Content Abstract 5 Tiivistelmä 6 Acknowledgements 9 List of abbreviations 11 List of original publications 13 Content 15 1 Introduction 17 1.1 Objectives and scope ............................................................................... 19 1.2 Research approach .................................................................................. 21 1.3 Research realisation and thesis structure ................................................. 28 2 Theoretical foundation: Innovation drivers, innovation types and success factors 31 2.1 Technology push and market pull innovation drivers ............................. 31 2.1.1 Integrated models ......................................................................... 32 2.2 Radical and incremental innovations ...................................................... 33 2.3 NPD success factor research ................................................................... 34 2.3.1 NPD key factors by landmarks ..................................................... 35 3 The success factors of technology push projects 39 3.1 TP Success factors by landmarks ............................................................ 41 3.2 TP research in ICT context ...................................................................... 44 4 Research contributions 47 4.1 Article I: Key factors of successful technology push projects in the ICT context: A review of the literature .............................................. 47 4.2 Article II: Explanatory definitions of the technology push factors ......... 48 4.3 Article III: A review of the Getting Real software development approach .................................................................................................. 51 4.4 Article IV: Developing technology pushed breakthrough: An empirical study ........................................................................................ 52 5 Discussion 55 5.1 Implications, validity and future research ............................................... 57 5.1.1 Implications .................................................................................. 57 5.1.2 Future research ............................................................................. 62 References 65 Original publications 69 15
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1
Introduction
Developing new and successful products to market is necessary for most companies (e.g., Balachandra & Friar, 1997; Cooper, 1994; Ernst, 2002). Because development processes are very risky and failure rates are high, it is obvious that the management of development-intensive firms must be interested in those factors that lead to successful innovations. In general, [critical] success factors are defined to mean the limited number of elements or areas where “things must go right” for the business to flourish. These areas of activities must be constantly and carefully monitored by management, and they are necessary in order for an organisation or project to achieve the end points that they try to reach (Rockart, 1979). Previous literature on new product development (NPD) has presented conflicting findings regarding two key concepts: technology push (TP) and market pull (MP) (e.g. Samli & Weber 2000, Herstatt & Lettl 2004). The TP school maintains that innovation is driven by science, whereas the MP school argues that user needs are the key drivers of innovation (Chau & Tam 2000). Most literature stresses that emphasis should placed be on MP (e.g. Myers & Marquis 1969, Langrish et al. 1972, Rothwell et al. 1974, Utterback 1974). Numerous successful TP products have been launched, however. Probably the most reputed TP innovator – or at least one of them – is the Apple company. “. . . But it was hard to explain what an iPad was . . . The first set of ads showed we didn’t know what we were doing.” “Some people say, ‘Give the customers what they want.’ but that’s not my approach. Our job is to figure out what they’re going to want before they do. I think Henry Ford once said, ‘If I’d asked customers what they wanted, they would have told me, ‘A faster horse!’’ People don’t know what they want until you show it to them. That’s why I never rely on market research. Our task is to read things that are not yet on the page.” Steve Jobs by Walter Isaacson (2011 pp. 529, 598) There are many similar kinds of examples. “We don't even know what it is yet. We don't know what it is. We don't know what it can be, we don't know what it will be, we know that it is cool.” Mark Zuckerberg’s character in the movie “The Social Network”. 17
“As a software development company, you have to act as a filter. Not everything everyone suggests is the right answer. We consider all requests but the customer is not always right.” Jason Fried & David Heinemeier Hansson, Basecamp. Discussions about whether TP or MP is more important are futile. There are plenty of success stories and even more failures related to both driving forces (e.g. Balachandra & Friar 1997). The current literature does not judge either concept. Instead, the concepts are linked strongly to particular innovation types: TP to radical and MP to incremental innovations (e.g. Samli & Weber 2000, Bishop & Magleby 2004, Herstatt & Lettl 2004, Brem & Voigt 2009). Radical innovations, also called ‘breakthroughs’, are innovations which change people’s lives permanently (Samli & Weber 2000). There have been many studies clarifying the success factors of NPD. Many of the key studies have not attempted to distinguish radical and incremental innovation. Because these two innovation types are not distinguished, the success factors of TP products are not explicitly known (Samli & Weber 2000). For instance, the meta-analysis by Ernst (2002) encompassing dozens of widely cited NPD studies, including Cooper and Kleinschmidt’s almost 30 papers, handles different types of innovation as one broad category. General NPD research, which does not take innovation type into account, is mostly too universal for studying the TP success factors. The quantity of NPD and innovation management research, representing different levels, different scopes and some with conflicting findings, means that we need to define a manageable set of success factors for further research. As Siggelkow (2007) states: “Theories and models are always simplifications. If they were as complex as reality, they would not be useful.” Cusumano (2010) follows the same philosophy to some degree, when speaking about his six principles for creating competitive advantage: “In reflecting on what I have learned, I concluded that a handful of principles – I have chosen six – appear to have been essential to the effective management . . . I have focused on principles supported by considerable theoretical and empirical research undertaken by a variety of scholars . . .” 18
1.1
Objectives and scope
The prime objective of this study is to present a compact set of success factors in TP projects in an information and communication technology (ICT) context1. The success factors of TP projects in ICT companies are revealed by studying the research on success factors at three levels. There are only a few research studies of the success factors specific to TP. Samli and Weber (2000) have generated and tested eight hypotheses of factors leading to breakthroughs. Bishop and Magleby (2004) categorised eight themes of TP development success factors in their literature review. It seems that there are only a small number of studies on TP success factors in an ICT context. Isaacs and Tang (1996) and Spivey et al. (1997) had analysed the most desirable context in their technology transfer studies but those were too caseoriented for deriving universal success factors. The TP concept is considered an important competitive advantage for R&Dintensive companies trying to create breakthrough products (Samli & Weber 2000, Herstatt & Lettl 2004). The research question in this study is: What are the success factors of successful technology push projects in ICT context? This has been answered by reviewing studies of success factors on three levels: NPD, TP and TP in an ICT context. The emphasis is on TP success factor research because we concluded that the success factors of TP products are industry independent. The first level of research is general NPD research. When using the epithet ‘general’, we mean NPD studies without any limitations of innovation drivers, innovation types, or industry. There are countless works about success factors at this level and it has been a significant research focus over the past four decades (e.g. Balachandra & Friar 1997, Ernst 2002). The second level is the success factor research limited to TP products. When we discuss technology push, or the TP concept, we are not limiting it to any specific 1 Definition of ICT context ICT (information and communications technology (or technologies)) is an umbrella term that covers all communication devices and applications, including computers and network hardware and software, mobile phones, various services and the applications associated with them (e.g., videoconferencing) but also more mature applications, such as radio and television (Asabere, 2012). We have used a narrower definition of ICT in this study by limiting it to computers, mobile phones and network application industries, including both hardware devices and software systems.
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industry. The quantity of the literature at this level is more manageable (e.g. Bishop & Magleby 2004). It is notable that the focus of NPD research has changed over the decades and it is clear that the MP models have received more attention from researchers and practitioners. MP projects are not within the scope of this study, however, and are therefore not addressed. The third level of research is the literature on research into success factors for TP projects limited to an ICT context. Even though the ICT industry is defined as one of the general purpose technology (GPT) industries (e.g. David & Wright 1999), there are only a few ICT-focused studies of success factor research. For example, only two out of ten TP studies in the meta-analysis by Bishop and Magleby (2004) are solely from an ICT context. The extent of NPD success factor research is presented in Table 1. MP research is not within scope of this study and it is marked with brackets.
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Table 1. Extent of NPD success factor research at different levels. Level
Extent
1. NPD
Countless
Model expressions ”The literature discussing success in product innovation is vast” (Balachandra & Friar 1997). ”NPD research has retained a high level of popularity over the last 30 years" (Ernst 2002). "Because of the numerous works available on this topic, a fact expressed in the many publications of review articles and meta-analyses" (Ernst 2002). ”Much of these new product research efforts have made no attempt to distinguish between simple product line extensions and breakthroughs” (Samli & Weber 2000).
(2. MP products)
Multiple
"Both MP and TP models have formally existed since the 1960s though MP models have clearly had greater attention from researchers and practitioners" (Bishop & Magleby 2004). "A large and rapidly growing literature on new product development [answers these questions] for the more incremental forms of innovation. But discontinuous innovation is very different in character…" (Lynn et al. 1996).
2. TP products
Several
”Several researchers and practitioners have identified factors that are associated or correlated with TP product development resulting in successful products” (Bishop & Magleby 2004).
3. TP products in ICT context Few
Only two out of ten TP studies analysed by Bishop & Magleby (2004) are solely in an ICT context (The author’s design).
1.2
Research approach
To study the widely recognised research question, a bipartite qualitative approach was used. The theory, as well as identification of the success factors were settled through an extensive literature review. The literature review (Bruce 1994) introduces an interpretation and synthesis of previous research (Merriam 1988) and discuss how the studied phenomenon relates to it (Leedy 1989). To extend the understanding of the studied success factors the author used a pilot case study to validate and uncover areas for theory building. An empirical approach with validation of the set of success factors was used as a qualitative case study method 21
(Eisenhardt 1989, Yin 2009, Runeson & Höst 2009). The research process was designed by applying the guidelines by Mackenzie and Knipe (2006), and is presented and summarised in a Table 6 at the end of this chapter. As Mackenzie and Knipe (2006) state, the research process is a cyclical, not a linear process. We therefore started the research process by defining the research problem and setting the research question. We found that to nominate a research paradigm, we have to first define the research problem (in Mackenzie & Knipe (2006) paper the paradigm was nominated first). The research paradigm has defined in many different ways and from many different perspectives (Mackenzie & Knipe 2006) but it could be condensed to a generally accepted way of thinking which guides the research steps. Similarly, different sources present the most common paradigms in slightly different ways (e.g. Mackenzie & Knipe 2006 vs. Cuba & Lincoln 1994). As per the guidelines by Mackenzie & Knipe (2006), our study is interpretivist and constructivist. Mackenzie and Knipe (2006) present four of the most common research paradigms as post-positivist/positivist, interpretivist/constructivist, transformative and pragmatic. In this study, the interpretivist/constructivist research approach was used. It tries to understand the world based on human experience, and the belief that reality is socially constructed. Interpretivist/constructivist researchers rely on informant views of the studied phenomenon, and compare it to their own experiences and background. The data collection will most commonly be performed in a qualitative way, in cases using the interpretivist or constructivist approach. A short comparison between the most common paradigms by Mackenzie and Knipe (2006) is presented in Table 2. The characteristics found in this study are bolded and italicised in line two. Table 2. Comparison of paradigms, methods and tools (adopted from Mackenzie & Knipe 2006). Paradigm
Primary method
Examples of data
Positivist/Post-positivist
Quantitative
Experiments, quasi-
Interpretivist/Constructivist
Qualitative
Interviews, observations,
collection tools experiments, tests, scales document reviews, visual data analysis Transformative
Qualitative with quantitative and
Diverse range of tools
mixed methods Pragmatic
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Quantitative, qualitative
Diverse range of tools
In this context, the qualitative case study method was chosen to gain a practical view of the research problem. Case study research was used due to the nature of the research question, and because there is little knowledge available in the research field addressed, the TP products in ICT industry (see Table 1). The author has mapped the study in two different ways, and both demonstrate that the case study was the most natural choice of research method for this research. First, in a qualitative research field, with deductive-inductive and subjectivist (interpretation centric)-objectivist (data centric) dimensions (Sarker 2007), we positioned our study to be obviously inductive without proven causality, and with influences from subjectivist and objectivist approaches. This is illustrated in Figure 1.
Fig. 1. Study mapping in the qualitative research arena (adopted from Sarker 2007).
Because our object was to interpret theoretical findings (success factors) through empirical testing, it was obvious that we needed to use an exploratory research method. The objective of exploratory research is to determine what is happening, to seek new insights and to generate new ideas and hypotheses for new research (Runeson & Höst 2009). The overview of the primary characteristics of the research methodologies (Table 3) by Runeson and Höst (2009) supports our choice of research method.
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Table 3. Overview of research methodology characteristics (adopted from Runeson & Höst 2009). Methodology
Primary objective
Primary data
Survey
Descriptive
Quantitative
Case study
Exploratory
Qualitative
Experiment
Explanatory
Quantitative
Action research
Improving
Qualitative
The case study research method (Eisenhardt 1989, Yin 2009, Runeson & Höst 2009) is used for investigating contemporary phenomena outside the controlled laboratory environment, and in its natural context. This allows researchers to understand how a phenomenon interacts with its context (Runeson & Höst 2009). Case studies can be divided into holistic case studies, where the case is investigated as a whole, and embedded case studies where multiple units of analysis are studied within a case (Yin 2009). To obtain a broad view of our research problem, we decided on the multiple case study method. For ensuring the credibility of the iterative research process, we applied the four tests by Yin (2009). The four tests compel a researcher to perceive construct validity, internal validity, external validity and reliability of the ongoing research. From a research process point of view, our study was carried out somewhat in common with that of, for example, Lettl (2005). In contrast to quantitative methods, such as surveys and experiments, the sample (=case) selection has to be happen intentionally (Eisenhardt 1989, Runeson & Höst 2009). We chose our cases from Finnish start-up companies operating in the ICT industry. The requirements for selection were: a) that the firm has developed a technology push product, and b) it must have a sort of evidence of commercial success. It should be noted that we did not investigate commercial cases in depth, we were instead interested in the experience and knowledge of the key persons behind the projects. The most common roles of the informants were as inventor, founder (of the firm), entrepreneur/partner and/or the CEO of the firm. As Eisenhardt (1989) notes, it is uncommon to plan the number of the cases beforehand, and this was also the case in our study. We had a rough idea, because of availability of resources and because of time constraints, but the final decision was made during the research process when we saw that saturation (when the incremental improvement to the theory becomes minimal) was achieved. Eventually, we investigated nine cases in total and during the process we found that the narratives of the informants were very similar, and the differences were due to 24
the size of the firms, not because of development processes. This number of cases fits well with Eisenhardt’s (1989) principle of case amounts. She claims that there is no ideal number of cases but that usually a number between four and ten is suitable. With fewer it is difficult to generate [or validate] a theory, and with more it is difficult to cope with the complexity and volume of the data. We have ensured the validity of the study by applying the four tests (construct validity, internal validity, external validity and reliability) devised by Yin (2009). Data collection was performed using semi-structured interviews (Myers & Newman 2007), which are common in case study research (Runeson & Höst 2009). A semi-structured interview is an incomplete script wherein the researcher has prepared questions in advance but there is still space for improvisation (Myers & Newman 2007). The question list (Sarja 2014) guided the discussions and the informants were encouraged to express their viewpoints, opinions and experiences without limitations. The 1.5–2 hour interviews were conducted between February and July 2015, and all were recorded, transliterated and thematically organised. The coding process implemented by transcribing all recorded informant’s answers verbatim to the tailored electrical form. The relevance of the success factors were estimated according to impression and experience of the informants, and based upon counting. However, we did not organise the factors in significance orders because this is a pilot study of the subject and because the informants represented only one nationality, and more data sources would required for doing that. As explained, the case firms operated in the ICT industry, representing both new hardware (HW) and software (SW) products. The interviewees were typically founders of their own businesses, and the firms were typically established round the technology pushed product idea. Half of the interviewees used a CEO title, and the rest of them were chosen an expert task and the title accordingly. The age distribution of interviewees was 28 to 56 years (mean = 42 years, median 46 years) and most had long years of experience in NPD activities before starting to work with their own innovations. Tables 4 and 5 describe the nine cases of the study. The tables can be read in such a way that Interviewee A represents Company A, and so forth.
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Table 4. Descriptions of the informants. Interviewee
Position
Founder
Partner
NPD
Entrepreneurship
experience
experience (years)
(years) A
CEO
B
R&D manager
C
CEO
D
CEO
X
16
3
33
6
X
1
10
X
17
3
X
E
CEO
14
0
F
Service director
X
X
10
8
G
Founder
X
16
12
H
CTO
X
28
3
I
CEO
X
6
3
Five TP cases involve hardware products, and four cases were software products. The business model2 in three cases was to sell to distributors and/or company users, but also directly to final users (A, C, I). It is noteworthy that, regardless of business model, in eight cases the final user can also be a private person. In other words, the product can be purchased by a distributor (A, C, I), or by a service provider (D, E, F, G, H). In one case the product was only for business use and was sold straight to business customers (B).
2
In this study the concept of ”business model” is narrowed to concern only the concepts of B2B and B2C. The thorough definition can be found for example from Seppänen & Mäkinen (2007).
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Table 5. Descriptions of the TP products in cases. Company
HW/SW
B2C
B2B
A
HW
X
X
B
HW
C
HW
D
SW
X
E
SW
X
F
SW
X
G
SW
X
H
HW
X
I
HW
X X
X
X
X
The research process design is summarised in Table 6. Table 6. Research process design (adopted from Mackenzie & Knipe 2006). Step
Examples of subjects
Selected subject
1. Research problem and research question Why some technology pushed ICT N/A
What are the success factors of
products succeed
successful technology push projects in an ICT context?
2. Paradigm nomination
Positivist, interpretivist,
3. Approach identification
Developmental, case study,
Interpretivist/constructivist
transformative, pragmatic Multiple case study
field study, experimental etc. 4. Data type determination
Quantitative, qualitative
5. Choosing data collection
Survey, observation, interview, Semi-structured interview
Qualitative
instruments/methods
experiment etc.
6. Identify where, when and who data N/A.
Intentionally selected 9 cases
will come from
according to case study methods (Eisenhardt 1989, Runeson & Höst 2009)
7. Data collection identification
N/A
Recording, transliteration, categorizing
8. Data analysis
Thematic analysis, statistics
Thematic analysis
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1.3
Research realisation and thesis structure
As described previously, the theoretical foundations and identification of success factors were settled through an extensive literature review. Based on the literature review, the researcher formed two articles (I, II). The TP success factors were identified in Article I. After completing the first article, the researcher came to the same conclusion as some other researchers (e.g. Balachandra & Friar 1997): the success factors found are not very exact; rather, they are descriptive vague topics. The researcher saw this issue as problematic; the success factors are too wide or may have many different meanings. The more detailed examination generated Article II, which proposes explanatory definitions for the success factors. For getting confirmation to be on the right track, the researcher carried out a slight validation, comparing the success factors with the successful breakthrough case presented in Article III. The empirical validation of the theoretical findings, a compact set of the success factors of TP projects, was conducted by interviewing the ICT industry professionals. The results of the interviews are presented in Article IV. The framing of the subject and the relationships of the articles are presented in Figure 2.
Fig. 2. The framing and original publications.
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The primary objective of this study is to present a compact set of success factors for TP projects in an ICT context. The thesis proceeds as follows. We first introduced the TP and MP concepts, innovation types and their connections with each other, based on related literature. The literature review continues in following section dealing with the main themes of the thesis, introducing not only previous literature but also how our study relates to it: how we derived the compact set of TP success factors, and the explanatory definitions of these descriptive vague topics. Finally, we assess the set of TP factors based on the empirical study performed with the help of industry representatives. We conclude by discussing the concepts of the TP success factor set, the main implications, validity of the study and future research proposals.
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2
Theoretical foundation: Innovation drivers, innovation types and success factors
This section provides an overview of the main topics of the study based on related literature. 2.1
Technology push and market pull innovation drivers
TP (Schumpeter 1939) and MP (Schmookler 1962) are the basic concepts for the driving forces behind innovations. There exist few synonyms in the literature for the concepts of technology push (e.g. science push, discovery push), and market pull (e.g. demand pull, need pull). The concept of MP suggests that market demand is the primary driver of innovation. In the concept of TP, the driving force for innovation is internal or external research and the goal is to develop new technology for commercial use. Two schools of thought have debated which the most advisable approach is. Traditionally, empirical research has been concerned with the question of how these approaches influence the success of innovation (Herstatt & Lettl 2004). Chidamber and Kon (1994) suggest that confrontation between the two approaches is due to different research objectives, definitions and models. Differences in problem statements and research constructs may also cause incongruity in research findings. Chidamber and Kon (1994) found that innovation research could be done at different levels; firm project, single innovation, industry, or even at national levels. Results found at a certain level are often inconsistent with results discovered at other levels. The four significant key studies of each school, most often cited in the literature, are (Chidamber & Kon 1994): Technology push: Mowery & Rosenberg (1979) Freeman (1982) Casey (1976) Pavitt (1971) Market Pull: Project SAPPHO (1974) by Rothwell et al. Meyers & Marquis (1969) Langrish (1972) Utterback (1974) 31
A comparison between the characteristics of innovation drivers is presented in Table 7. Table 7. Innovation driver comparison (adopted from Herstatt & Lettl 2004, Gerpott 2005). Attribute
Technology push
Technology uncertainty
High
Market pull Low
R&D expense
High
Low
R&D duration
Long
Short
Time to market
Unknown
Known
Innovation process
“Probe and learn” type
“Stage-gate” type
Market-related uncertainty
High
Low
R&D customer integration
Difficult
Easy
Customer experience
None present
Present
Customer education
Usually necessary
Not necessary
Market research type
Qualitative “exploratory” research
Quantitative conventional market
Need for changing customer
Extensive
Minimal
research behaviour
Herstatt and Lettl (2004) explain that the degree, or newness, of innovation influences the development investments of both time and money, to the certainty level of technology and market. Lynn et al. (1996) state that the certainty level of technology and market causes different development processes: experimental probe-and-learn-type processes in TP cases and confirming stage-gate-type processes in MP cases. Knowledge of the needs of the market is different for both drivers. The TP strategy represents future markets that are difficult to predict and the MP strategy represents the current market situation. The market research methods employed are therefore also different: exploratory qualitative for TP and conventional quantitative (e.g. surveys) for MP (e.g. Herstatt & Lettl 2004). The TP concept is traditionally linked with radical innovation, whereas MP is linked with incremental innovation (e.g. Herstatt & Lettl 2004, Gerpott 2005, Brem & Voigt 2009). It can be said that the more radical the innovation, the more customer behaviour must change in order to adopt the innovation (Schiffman & Kanuk 1997). 2.1.1 Integrated models Even though some firms may be on the right track by focusing only on TP or MP, some researchers (e.g. Brem & Voigt 2009) suggest that firms should not focus on 32
an one-sided innovation strategy in the long term. Strategy decisions should be made case by case, or preferably, using a combination of both strategies (e.g. Freeman 1982, Zmud 1984, Munro & Noori 1988, Ulrich & Eppinger 2008). Many researchers (e.g. Souder 1989, Herstatt & Lettl 2004) emphasise that innovation usually consists of hybrids of both concepts. Freeman (1982) found that the ability to connect technical and market opportunities is a success factor of innovation. The balance has been on market-related activities in TP projects (e.g. Herstatt & Lettl 2009). Ulrich and Eppinger (2008) have defined the known generic product development process, which somewhat follows the MP process concept. They simplify TP thought by adding technology-market matching to the first (out of six) phases (planning) of the [market pull] process. Even recent NPD literature does not present a black and white case in the TPMP debate, leaving some space for interpretation at the case level (Herstatt & Lettl 2004) and providing a change to combine both strategies. As mentioned before, many successful firms in the market adhere to the TP approach, either intentionally or accidentally. Two excellent examples on different scales are Apple (Isaacson 2011), who did no market research, and 37signals (Sarja 2012), who defend their stance of not listening to customers in the development phase. As noted before, the TP strategy dominates radical innovation and MP dominates incremental innovation. 2.2
Radical and incremental innovations
Innovation is generally defined as a new technology or combination of technologies that offer valuable benefits to the user. The difference between radical and incremental innovation is the degree of novelty. Radical innovation involves the development of significantly new technologies or market ideas previously unknown, or that require remarkable changes to what currently exists in the market. Incremental innovation is an extension to current products or existing processes (e.g. McDermott & O’Connor 2002). Even though the definition of radical innovation varies in the literature (e.g. Green et al. 1995, McDermott & O’Connor 2002), one valid and measurable definition by Green et al. (1995) incorporates four dimensions: technological uncertainty, technical inexperience, business inexperience and technology cost. Many researchers also add the change dimensions: change in customer behaviour (e.g. Samli & Weber 2000) and change in the existing market (e.g. McDermott & O’Connor 2002). 33
As radical innovation is a consequence of TP development strategy and incremental innovation is a consequence of MP strategy, the characteristics of both types are identical with development strategies (see Table 2). By collating and summarising the characteristics, it is clear that the development of radical projects has higher risks, but also higher profit expectations (e.g. Christensen 1997, Samli & Weber 2000). The radicalness of innovation projects is a fundamental element, which has been referred to and examined under many different labels (Green et al. 1995). The most well-known synonyms for the concepts are presented in Table 8. Table 8. Synonyms of innovation types. Radical
Incremental
Discontinuous
Continuous
Breakthrough
Line extension
Revolutionary
Evolutionary
Pioneering
Routine
New-to-the-world
Extension
Discovery push
Modifying
Original
Adapted
Successful radical innovations are rare when compared with incremental innovations but two aspects make it an interesting research topic. If it succeeds, it is a competitive advantage for the firm (e.g. Lynn et al. 1996, Lynn & Reilly 2002) and incremental innovation would not exist without radical innovation, because the former always follows the latter (Utterback & Abernathy 1978). 2.3
NPD success factor research
New product development and commercialisation of innovation has been an important research topic for decades, because it is a core task for developmentintensive organisations (e.g. Balachandra & Friar 1997; Ernst 2002). Because of rapidly developing technologies, stiff competition and shifting markets, it is also a very complex and difficult process (Cooper 1994). What we mean here by NPD success factor research, is a literature of general level development activities without distinguishing the innovation drivers and innovation types. The framework of NPD success factor research is illustrated in Figure 3.
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Fig. 3. The framework of NPD success factor research
2.3.1 NPD key factors by landmarks We have chosen two NPD-related landmark papers for closer examination: Ernst (2002) and Balachandra and Friar (1997). These NPD-related papers are clearly focused on research of the success factors. Both papers are meta-analyses in nature giving broader outcomes of the topic. They are acknowledged and widely cited within a large range of source material including elementary studies of NPD. Ernst Ernst has reviewed dozens of NPD-related papers including Cooper and Kleinschmidt’s 28 papers. The success factor in the categorisation mode used by Ernst is that originally used by Cooper and Kleinschmidt (1995). The defined categories are NPD process, organisation, culture, [senior] management commitment and strategy. The NPD process category is universal by nature and is also slightly misleading. It does not take a stand for a development process itself. Most factors sorted to this category are marketing related: the continuous commercial assessment during all phases of the NPD process, the NPD process orienting to the market needs, the 35
distinguishing between market orientation and customer integration into NPD and the quality of planning before the development phase. The individual aspects of the organisation category are explicit: cross-functional project team members; strong, responsible and committed team leaders; responsible and committed project team members; intensive internal communication during the project and finally, the correct form of project organisation. The culture category refers to the atmosphere of innovation within the company. The objective is to create systematically an innovation-friendly and entrepreneurial climate within the firm. Enabling work with their own and other unofficial projects and enabling the realisation of creative ideas can be a way to achieve that objective. The role and commitment of senior management addresses mostly the question of adequate resource allocation for the project. According to Ernst, new product strategy has been barely examined and it requires further research. The project must be defined and the project goals must be clearly communicated. The project must have a strategic focus, which gives overall direction to the individual NPD projects and it must be a part of a long-term NP portfolio. Balachandra & Friar Balachandra and Friar reviewed more than 60 papers in the fields of R&D projects and product innovation. The authors categorised the found factors according to the method used in marketing strategy studies (Aaker 1992). The categories are market, technology, environment and organisation. The original success factor list identified by the examined material was long, totalling 72 factors. The final 14 factors chosen were those cited by four or more studies. This selection method omitted single and case-related factors. The noteworthy result is that the selected categorisation mode was not perfectly suitable after screening the factors, because there was no factor related to technology and only one related to the environment. Most of the success factors found by the authors are organisation related and few of them are market related. The findings of landmark papers are submitted in Table 9. It can be seen that the aspect of these meta-analyses is somewhat different. Ernst (2002) settled on finding success factors at the organisation level, whereas Balachandra and Friar also took account of external factors. The same principle goes for the original categories by Aaker (1992) and by Cooper and Kleinschmidt (1995). It can be said, that organisational-level factors are influenced by the organisations own management but that the external factors are partly given. 36
Therefore, all factor categories used by Ernst (2002) can be included in Balachandra’s category named organisation. Table 9. NPD level success factors. Market
MA¹ Technology
related
related
Probability of
BF²
tech. success Market
MA Environment related
MA Organisation
MA
related
Availability of
BF High level mgmt. support
raw materials
Resource allocation
BF,E³
BF
Emphasise marketing
BF
BF
R&D process well planned
BF,E
BF
Marketing & tech. are
BF, E
existence Need to lower cost Competitive environment
strengths/cross functional team Timing
BF
Commercial assessment,
BF, E
create market interphase, customer integration, process orienteering to market needs Training & experience of staff
BF
Project staff commitment
BF,E
Team leader capability and
E
commitment Tech. strategy tied to business
BF,E
strategy Project definition, strategic focus,
E
NP portfolio Internal communication
E
Innovation friendly climate
E
Entrepreneurial climate
E
Form of the project organisation
E
¹ meta-analyses ² Author: Balachandra & Friar (1997) ³ Author: Ernst (2002)
It can be concluded that the findings of the NPD literature, without distinguishing the innovation driver types, are in most cases organisation and process related and do not observe the success factors related to project outcome, e.g., technology or product.
37
The impetus for all NPD processes comes from TP or MP innovation drivers (Herstatt & Lettl 2004; Brem & Voigt 2009). The focus of this study is in technology push research.
38
3
The success factors of technology push projects
In the NPD literature, for example, the widely cited works of Cooper (1979–1994), Cooper and Kleinschmidt (1986–1996) and the landmark papers of Balachandra and Friar (1997) and Ernst (2002), no attempt has been made to distinguish between radical and incremental products, or to acknowledge that the emphasis has been on MP projects. The number of studies on success factors related to TP projects is limited. We have chosen two meta-analyses landmark papers for closer examination: Bishop and Magleby (2004) and Samli and Weber (2000). Figure 4 illustrates the framework limited to success factor research of TP products.
Fig. 4. The framework of TP success factor research
These two landmark papers were chosen for several reasons. First, they are focused solely on TP projects. Secondly, the perspective of both papers is clearly to trawl success factors. Thus, the focus of the selected papers is very similar to ours. The only difference is that the selected papers are not limited to a certain industry, whereas we consider the ICT context only. Both papers are wide-ranging and cover several research targets. Samli and Weber researched 30 separate long life cycle radical product cases and Bishop and Magleby reviewed 10 different level papers 39
concerning the success factors of TP products. Finally, both papers are relatively new in this topic area. The authors of both papers have ranked their findings according to relative importance by using justified metrics. These findings are based on specific cases and in different contexts; thus it is clear that their findings are comparable only within the meta-analysis but not between them. Bishop and Magleby researched the evolution of TP models for further research. They also studied the success factors of TP-developed products and thematized them into eight categories for further TP model research purposes. They studied 10 separate sources of differing natures, representing different levels of studies. The sources are from the period 1987 (Paul) to 2003 (Himmelfarb). The meta-analysis consists of: –
– – –
Five journal articles. One out of five articles is poor according to today’s standards. Its length is only two pages, has no quotes and does not reveal how the results and conclusions are achieved. One article published only on the Internet, which no longer exists. One panel discussion note (linked with a journal article by the same authors). Three business books.
The varying level of sources over a long period confirms the understanding that the quantity of TP-focused success factor research is limited. From our perspective, it is notable that only two studies in this meta-analysis were wholly within the ICT context. Samli and Weber researched 29 separate long life cycle radical product cases. They make a clear distinction between incremental and radical innovation research and they lambasted other NPD research for not distinguishing the innovation types but keeping them as one broad new product category. The authors chose 30 long life cycle (over 10 years) products from the breakthrough innovation list identified by the Business Week magazine (one company did not take part in the study). They tested their hypotheses by interviewing the marketing division staff of the organizations behind the chosen products. Six out of eight hypotheses were supported regarding the success factors of radical innovation. From our perspective, it is notable that none of researched cases was within our narrower limited ICT context (see our definition of ICT context). The environments of the landmark studies are presented in Figure 5.
40
Fig. 5. The landmark TP meta-analyses.
3.1
TP Success factors by landmarks
Bishop and Magleby Bishop and Magleby state that each of the papers they studied was written by authors of different backgrounds and was aimed for different audiences. The backgrounds of the authors varied from engineering, marketing, consulting and R&D management. The background of the audience ranged from practitioners to researchers. The same principle works between both landmark papers. Bishop and Magleby divided the success factors they found into eight categories. According to the authors, the success factors are as follows, arranged in order of significance: 1.
2.
3.
There is a focus on customer/end user needs Customer or end user needs were considered during the development of the product. Internal/external networks were used Networks internal and/or external to the company were used during product development, which were beyond interacting with customers and end users. There is management support
41
4.
5.
6.
7.
8.
There existed support from the management either directly or through methods, such that management generally have control over such as the organisation model. The development team is dynamic, motivated and/or talented There was a high level of expertise, motivation and/or ability within the product development team. A combination of MP and TP is used Both MP and TP methods were used in the same product development process beyond simply including customer and end user needs with TP elements. The market is developed during or directly after product development The market was developed, instructed or prepared simultaneously with development of the product. The technology offers a clear advantages The product offers a clear advantage over other, similar products, directly because that technology was the basis for the development. Alternatives were examined carefully Alternative technologies, products and markets were examined carefully by the product developers during development.
The authors state that because of the diverse audiences and researchers, the success factors are written using terminology that is inconsistent. Perhaps because of this, the developed factors are intangible by nature and somewhat difficult to measure, define and even distinguish from each other (e.g. factors 1, 5 and 6). For instance, roughly speaking, if we are using a combination of TP and MP, we are focusing on customers and we are developing for the market. Samli and Weber Samli and Weber constructed a series of eight hypotheses for testing the relevance of their universal model of breakthrough development. Six out of eight hypotheses were supported. The hypotheses are introduced in order of significance (the pair H2 & H3 is equivalent). 1.
42
Technological push results in new products that are not readily adopted. The development of technology push products is a long-term action. From the firm’s point of view, it means a commitment to technology push projects in the long run.
2.
3.
4.
5. 6.
The degree to which a new product is a breakthrough will increase the length of time before the product is adopted by the market, i.e., technophobia. The novelty of technology push products affect the adoption time by the market. In reference to the target of our study, we see this factor as very close to the previous one, technophobia, such that we discuss them as one factor. The greater the percentage expenditures on new product development and related research, the greater the number of new successful products introduced. More than 62% of the respondents to the landmark papers spent over 20% of their total budget developing new products. The level of a breakthrough has a direct correlation with the longevity of the product. Even though technology push products are not accepted quickly by the market, they display longer life cycles than minor product developments or line extensions. Technophobia This factor is combined with the degree of novelty factor (nr. 2). Products that fill an unrecognised need will have greater longevity than those that do not. If the firm has no knowledge of the market and it is proceeding completely with an internal technology push, it is not likely to be successful.
The order of significance is calculated in a different way in each meta-analysis. Therefore, the order is valid only inside the same meta-analysis and it is not comparable between the meta-analyses. In order to simplify the factors of both papers and to enable links between them, we have thematized all the findings according to common factors. This was done by thematizing the found success factors. Thematization enables a comparison of the occurrence of certain themes (Eskola & Suoranta 1998). We compiled four different categories: market, product, management and organisation [related] factors. The different aspects of management- and organisation-related success factors existed so clearly that we distinguished them as separate categories. We also shortened the findings for simpler representation. The summary of TP success factors is illustrated in Table 10.
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Table 10. TP Success factors. Market related
MA¹
Product related
MA
Management related MA
Organisation
MA
related Focus on
BM²
customer needs MP methods
TP for difficult
SW
Management support BM
Networking
BM
SW
Degree of funding
Project team
BM
adopted BM
Life cycle
used
SW
skills
Market
BM
development
Fill an
SW
unrecognised need
Alternative study BM
Technological
SW
advantages Adoption time/
SW³
BM
technophobia ¹ meta-analyses ² Author: Bishop & Magleby (2004) ³ Author: Samli & Weber (2000)
3.2
TP research in ICT context
The ICT context in our study is limited to hardware and software products in computer, mobile phone and network applications industries only. Only two studies out of the ten in the meta-analysis by Bishop and Magleby were solely within the ICT context (Isaacs & Tang 1996 and Spivey et al. 1997); moreover, one study had one ICT case study out of four within the desired context (Lynn et al. 1996). The other landmark paper by Samli and Weber had no cases within an ICT context. They categorised four researched radical products as “Telecomm.” applications but those products do not fit our definition for ICT (fibre optic phones, a book-size video camera and two different HI-FI TVs). We have gathered the success factors within an ICT context categorised by Bishop and Magleby. The aforementioned two ICT-related sources of the study give the following factors: 1. 2. 3. 4. 5. 6. 44
Internal/external networks are used There is management support There is a focus on customers/end users The development team is dynamic, motivated and/or talented The market is developed during or directly after product development The technology offers clear advantages
Limiting the context from general TP projects to ICT projects causes a change in factor category ranking. Factors 1 and 2 are referenced by both studies and factors 3–6 are referenced by one or the other. The order of the remaining factors is according to the original meta-analysis. Table 11 represents the factors according to the familiar categories. Some conflicting issues led us to constitute a premise. First, the quantity of source material is too slight in terms of our target; a concrete set of the success factors. The discovered factors are intangible by nature for deriving concrete factors. Paradoxically, the findings of these two studies within an ICT context have already covered six out of the eight factor categories, which were defined without the industry limitation when all ten studies in the meta-analysis were investigated. Comparing the general TP research and the TP research limited to an ICT context, we can conclude a premise: The success factors of the TP products are industry independent. Cusumano (2010) made same kind of assumption with his Six Principles [of effective management of strategy and innovation]: “What I offer is a selective list, mainly from the automobile, computer software, telecommunications, consumer electronics, and Internet service industries. But, because of their generality, I am convinced that these principles provide essential lessons for managers in nearly any industry.” In practice, the premise means that we can constitute the list of the success factors of ICT-related TP products with TP research in any industry. The industry independent success factor set of TP products was discussed in chapter 3.1. Table 11. TP Success factors limited to ICT industry by landmark studies. Market related
Product related
Management related
Organisation related
Focus on customer
Technological
Management support
Networking
needs
advantages
Market development
Development team skills
45
46
4
Research contributions
This chapter summarises the main results and contributions of each article included in this thesis. These articles represent how the success factors were defined, starting from the existing literature and concluding with the empirical test. 4.1
Article I: Key factors of successful technology push projects in the ICT context: A review of the literature
The first article tried to answer to the research question: What are the success factors of successful technology push projects in ICT context? As per its title, the article is a literature review. The writing process guided the author deeper into the NPD research genre by distinguishing different types of innovation drivers and types of innovation alike. The article is compiled so that at first the essential concepts of NPD research are discussed. This was done in the same way as in this thesis (see Chapter 2). The need for NPD is justified from the perspective of a development-intensive firm. Different innovation drivers (TP, MP) are discussed, as well as radical and incremental innovation types, and their connection with each other. Radical innovation is always a consequence of TP development strategy and incremental of MP strategy (Fig. 3). Secondly, the success factors were identified using existing literature. The amount of available research was vast (see Table 1). Innovation drivers were distinguished for approaching the research question. This approach is supported by many researchers who stress that different innovation divers and types need to be studied separately because they have different motivations and backgrounds. It is reported that, according to available research papers, the focus of previous research has been in MP concepts, and there is less but more manageable TP research literature (see Table 1). From this manageable amount of TP literature, two metaanalyses were chosen as landmark papers. Meta-analyses are the research papers that already contain the results of several other studies. The key results of this article, the TP success factors, were collected from these landmark papers. It is notable that this article also attempted to limit the industry studied to ICT, but the residual material was minor and partly low-grade, and finally the analysis was performed without industry limitation. In an article (and thesis) writing moment the best understanding was that the TP success factors are industry independent, and this theory is also supported by some other researchers (e.g. Cusumano 2010). After 47
thematic analysis of the previous research the first version of TP success factors was defined. The key results of this article are as follows: 1.
2.
The TP success factors found can be organised in four different categories. These categories are market, product, management and organisation related success factors. A total of 13 different success factors were identified. Five (out of 13) factors are market related, four factors are product related, and two factors were categorised under management and organisation.
The identified categories and success factors were introduced in Table 10 (chapter 3.1). At the end of article three interesting standpoints were discussed. At first, the author was not satisfied about the rigour of the success factors found. The factors found are not exact, but are rather descriptive general topics. This makes the use of the factors somewhat problematic; the factors are either too wide or can be discussed in many ways because they may have many different meanings. This was also noted by other researchers (e.g. Balachandra & Friar 1997). Therefore the further research of the topic is thus recommended in the article. The success factors should be divided into smaller pieces and the exact practical meanings should be defined (see Article II). Then, the success factors at the NPD level [as far as they depart from TP factors], that is to say, the business factors without innovation driver (TP) limitations, are good general level guidelines for managing project-oriented organisations. The article recommends that before starting to develop a TP product (considering TP success factors), a firm should ensure that the basics – the NPD level success factors – are taken into account. The author reminds readers that the thematisation of the factors is not a black and white process and the divisions between the themes are very thin lines. This is because the factors are indefinable by nature and it is also a matter of research angles and individual thinking. 4.2
Article II: Explanatory definitions of the technology push factors
The second article explains the TP success factors introduced in Article I. Because the found success factors are on a general level and ambiguous in nature, the author 48
found that further study is needed to provide specific practical aims for them. Specific definitions are needed for two reasons. First, the vague topic type factor does not give any real fix to the practitioners. Secondly, the empirical test for the factors is impossible to execute at this level of rigour. For example, the research design process, including the data collection (e.g. interview question list), cannot be planned without more detailed level knowledge. In Article II all success factors are divided into smaller pieces and then the explanations are gathered from the existing literature. The key results of this article are as follows: 1. 2.
The explanatory definitions of the TP success factors are introduced and discussed. The explanatory definitions enables empirical tests to be planned for the success factors3
A short summary of the explanatory definitions of the TP success factors follows. Market related success factors –
–
–
MP methods used: MP thought is not a method, but an innovation driver approach. It is also an umbrella term covering most of the market-related factors. The product development process should be the same regardless of the innovation driver (TP or MP). In TP case, technology-market matching must be added to the planning phase of the (MP) development process (e.g. phase 0 in the generic development process by Ulrich & Eppinger 2008). Focus on customer needs: Most literature about NPD, including TP-focused literature, stresses that customer needs must be identified at the beginning of the development process and that customers need to be segmented. The output of identified customer needs of the target segment should be a constructed list organised in hierarchical order, with importance weightings. Market development: The term ‘market development’ has many definitions. In a TP research context we have adopted the growth strategy model by Ansoff (1957) (aka ”Ansoff model”) with slight correction to one definition. In a case
3 After finalising this article, the researcher was able to compile the interview question list for the industry representatives. The model for the question list was published in the researcher’s licentiate thesis (Sarja, 2014) and as an attachment in Article IV. The results of the interviews are introduced in Article IV.
49
–
–
of TP products, two sub-concepts are ”product development” (new products for existing markets) and ”diversification” (new products for new markets). Market development must be done simultaneously with the product development. Alternative study: Alternative study must be conducted simultaneously with other sub-processes at the beginning of the product development process. Alternative study is a wider process than just competitor analysis. The business should not be defined in terms of product types but in terms of customer needs to be served. This thought encourages management to study business and growth opportunities, considering not only direct competitors but also indirect solutions (substitutes) and potentially competing solutions. Adoption time, technophobia: These two concepts, adoption time and technophobia have a clear connection in the field of NPD research, particularly when speaking about TP products. The research community emphasises a commercial motivation for user-friendliness in hardware and software due to the attempt to appeal to technophobia and shorten adoption time.
Product related success factors –
–
–
–
50
TP for difficult to adopted: TP driven products typically take longer to be adopted by the majority of customers. This factor is the adoption time domain from a developer’s perspective. The longer the adoption time from a firm’s point of view, the longer term commitment to a project, especially in terms of resources. Resource planning is needed throughout the whole development and adoption time. Life cycle: The expected life cycle of TP product is longer than that of incremental MP products. Economic and resource planning must be undertaken for the entire life cycle period. Filling an unrecognised need: This factor summarises somewhat the factors ”focus on customer needs” and ”market development” (This factor is not addressed in Article IV because of its insignificance). Technological advantages: The development team’s ability to create a TP product that has overall benefits compared to other similar solutions and has been developed on the basis of technology.
Management related success factors – –
Management support: The most important support from management is to ensure adequate financial and human resources for generating TP products. Degree of funding: The projects must be prioritised in terms of the success of the firm and be realisable with budgeted resources.
Organisation related success factors –
–
Project team skills: Team skills are the consequence of cross-functional knowhow. A product development team should have expertise at least in marketing, design and manufacturing functions. Networking: Networking is the way to consolidate in-house know-how and resources. The other benefits are risk and cost sharing, access to new technologies and markets and attempts to shorten development time. It can be done, for example, with customers, suppliers, competitors, other players in industry, research institutes and in the public sector. Because of conflicting findings in the literature regarding networking in NPD and increased success, Ledwith & Coughlan (2005) suggested a three-variable (who? why? skills?) framework for managing networking for reaching successful collaboration.
The researcher proposes to test the discussed TP success factors in breakthrough case studies. 4.3
Article III: A review of the Getting Real software development approach
The objective of the third article is to validate partly the discussed success factors. It is based on a wider study by the researcher (Sarja 2011). A software developing firm named Basecamp, formerly known as 37Signals, is a good example of the TPoriented firm in many ways. First, technologies are combined in a new way in its products (e.g. in the Ruby on Rails platform). Second, the products are differentiated from those of competitors by simplifying them in a radical way. The key persons of the firm call this ”underdoing the competition”. This closely resembles Bower and Christensen’s (1995) disruptive technologies pattern: neither purely technical or performance vice the disruptive technologies are not the most advanced, but those that are simpler, cheaper, reliable and easier to use. In many 51
cases a simplified design also means new means of technology combinations, and is supported, for example, by the Agile Manifesto (simplicity – the art of maximising the work not done – is essential) and the heuristic evaluation method of Nielsen & Mack (1994). Thirdly, the case firm has created whole new processes, such as the software development approach called Getting Real (Sarja 2011). Fourth, one of the main principles of the firm has been not to conduct market research or to communicate with customers in the development phase. Article III itself is a wider description of the case firm and its product development operational principle. The success factors discussed in Articles I and II are partly validated (Sarja 2014) using the information in Article III before proper empirical validation (presented in Article IV). The success factors ”focus on customer needs”, ”technological advantages” and ”lowering adoption time” are supported by the case. 4.4
Article IV: Developing technology pushed breakthrough: An empirical study
The fourth article describes the empirical validation of the discussed TP success factors. The goal of the validation is to determine the relevance of the success factors and possibly define new ones. The article is based on nine qualitative semistructured interviews with experienced new product developers and entrepreneurs. The case selection was done intentionally (Runeson & Höst 2009) from a theory building point of view, instead of random sampling (Eisenhardt 1989). To carry out the study, we determined that the selected case firms (1) must operate in the ICT industry, (2) must have a self-developed TP product, and (3) the product must be launched and already in the market. These informants represented the different sizes of Finnish ICT start-up firms with breakthrough products and the interviewees were typically the founders of their own businesses. The typical title of the interviewees was CEO and the mean age was 42 years. Five of the firms were hardware producers and four firms were software development companies. The interview question list was based on the study of Sarja (2014) with small insertions (see also Chapter 4.2), and included one to a few questions about every success factor. The informants were then given opportunities to agree, disagree or comment on the discussed success factors. One notable point is that the number of cases was not planned at the start of the study, but when the theoretical saturation point (Glaser & Strauss 1967) and minimisation of the incremental improvement (Eisenhardt 1989) of the study was reached. It was notable after the first few cases 52
that the results of the interview were repeating themselves. In the end, the study was conducted with nine cases, which is supported well by the principle of Eisenhardt (1989): a number of cases between four and ten works well. The key results of this article are as follows: –
–
–
The first change to the set of success factors was to remove the factor ”fill an unrecognised needs”. The researcher did not see the value of this factor. This was supported by the community (e.g. Samli & Weber 2000), which stated that both the market and customer needs must be studied by the developers, and was covered in the market-related success factors section (see also Chapter 4.2). The number of success factors was thus reduced to 12. It was concluded that the coverage of all twelve success factors was supported by interviews in two ways. At first, all informants were able to respond to all questions and discuss all factors. Then, all responses to the open question (Can you mention any other [than discussed] success factors which have influenced the commercial success of your firm’s products?) started by repeating already discussed factors instead of defining new ones. After the interviewers redirected the conversation, the discussion turned to new proposed factors. Most of the proposed success factors were just a case-specific ideas suggested by a single informant only, however, three generalised thoughts arose from more informants, namely scalability, visibility and timing. Scalability was raised by half the interviewees. They saw that the characteristic of scalability was necessary in consumer product groups. It was also noted that a scalable product will solve the problem of many different customers. The visibility factor was mentioned in many cases. The informants started to publicise and pre-sell products already in development phase. It was also reported that the characteristic of visibility helped to create a phenomenon around the solution and thereby in funding negotiations. In more than half cases, successful timing was seen as a success factor. In this context, timing was seen from a technology and product maturity point of view. The technology in use should be ready enough for commercial solutions, but a rough version of the product is enough for market entry.
As mentioned, all twelve success factors were supported by the informants, and three more factors arose during the study. The factor fill an unrecognised needs was removed. We positioned the new success factor scalability in the product related success factor group because it was clearly a planned characteristic of a developed 53
product. Visibility and timing were strategic management decisions and naturally management-related factors. The complete set of empirically validated TP success factors are presented in Table 12. Table 12. TP key factors after the study. Market-related
Product-related
MP methods used
TP for difficult adopted Management support
Management-related
Project team skills
Focus on customer
Life cycle
Degree of funding
Networking
Technological
Visibility
needs Market development
advantages Alternative study Adoption time and technophobia
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Scalability
Timing
Organisation-related
5
Discussion
In this chapter the main results, implications, validity and future research opportunities are discussed. The research question, what are the success factors of successful technology push projects in ICT context, is very broad and universal by nature. In the beginning we thought that we would find the answer in the literature review, and we would be able to answer the question in Article I. This was not the case, however. Instead, we were approaching the final answer all the way from the first literature review to the empirical validation. That way was covered, finally, all four articles (I-IV) included in this thesis. The outcome of that literature review was a set of vague, ambiguous themes instead of clear interpretative factors. Naturally, we were not happy with that result (Article I). We needed to divide the factors into smaller pieces and continue the literature review to obtain reasonable content for the factors (Article II). Only then were we able to plan research tools (the interview question list in this case) for empirical testing. Before the proper empirical study we made a lighter version comparing the results to some of our previous studies (Article III). During the empirical study (Article IV) we removed one (out of 13) success factor from the introduced set, and we added three new success factors to the set which were not mentioned in the literature. The researcher sees the research question, regardless of its universality, as very important to the whole ICT industry. The answer to the research question was therefore formed in all ways and sharpened at every step. The final answer, based on the literature review and empirical validation, was introduced in Article IV. It consists of the set of 15 separate success factors, the elements and areas where “things must go right” for a business to flourish. How did we conclude the discussed results? In the theoretical part of the study, we made a broad literature review of related works. These related works are presented in Articles I and II. We started by analysing the literature of the NPD success factors on a general level without distinguishing the innovation drivers or types. For including different types of innovations to the same research is strongly judged e.g. by Samli & Weber (2000). We then concentrated on the literature of the TP success factors. As mentioned before, with the support of many researchers (e.g. Bishop & Magleby 2004), we found that there has been much less TP success factor research. Finally, we tried to limit the TP research to the ICT industry only. In that case we realised that there is not enough literature, and that the quality of the existing few studies was too poor to draw reliable conclusions. All our conclusions were therefore based on the TP level (TP products without industry limitation). The 55
industry independent thought in innovation study discipline is a current understanding (supported by, e.g. Cusumano 2010). The empirical part of the study (Article IV) introduced three new success factors that had not been mentioned in the literature. All these exercises arose following speculations and limitations: –
–
–
–
–
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The success factors at NPD level [as far as they depart from TP factors], that is to say, the business factors without innovation driver (TP/MP) limitations, are good general level guidelines about how to manage project-oriented organisations. Article I recommended that before starting to develop a TP product (considering TP success factors), a firm should ensure that the basics – the NPD level success factors – are taken into account. We concluded that the industry independent thought is a current understanding in innovation research discipline. Actually, there is not any scientific evidence for this. The reason for this conclusion is simply that, as explained, there are no TP success factor research papers directed to a particular industry (e.g. ICT). This deficiency could be a good topic for future research (see 4.1). We think that it is very likely that there are some success factors specific to the ICT industry only, but a separate research approach and study would be required. After completing the entire study the researcher formed an impression that success factor research longs for new perspectives (hoping this study may provide that). This can be seen in the following things. First, as explained, three (out of 15) new success factors arose during the empirical study. All these three factors (scalability, visibility, and timing) are generalised characteristics that are currently noted and discussed, but the literature has not identified them. It seems that after early enthusiasm, the number of publications decreased radically. This explains why the literature source material in this study is slightly old (typically from the 1990s and 2000s). On the other hand, the original Article IV responds to this shortage. This study did not reveal any facts that would find the correlation between NPD and entrepreneurial experience, and the success of the business. This was not included in the area of our interest, and so is best treated only as interesting background information. We grouped the factors found for four categories: market, product, management and organisation [related], however, thematisation is not a black and white process and the divisions between the categories are very thin lines. Depending on the research angle, a single success factor can be thematised differently. It is not possible to put success factors in order of importance with
–
5.1
this level of information, but it can be concluded that the balance is on marketing related success factors. The largest number of factors belongs to that group, and perhaps it is the most researched discipline. It is notable that the achieved results are at a general level. We studied the entire set of success factors empirically, knowing that every single case or every single success factor would be an adequate target for its own study. In that way it would be possible to receive more detailed knowledge about each factor’s function, efficiency and the application of the factor as part of a firm’s development processes. As discussed, the common factor in our case firms was that they are all startups that had already placed their product on the market. Still they represented different sizes resource-wise (e.g. head count, turnover). Some success factors do not sit very well with small firms that have only one product and where the management are also owners. For example, the questions regarding management related success factors would apply better to bigger and older players in market with hundreds of employees or more, and several product projects, rather than to start-ups. Implications, validity and future research
The implications and validity of this study and future research proposals are discussed in this chapter. 5.1.1 Implications The objective for this study was to present a compact set of success factors in TP projects in an information and communication technology (ICT) context. To this end, we developed theoretical arguments to justify the set of success factors within the ICT industry, and in turn, explored empirical support of the theoretical grounding through a multiple case study. We studied the innovation success factor literature at three levels: NPD, TP and TP in an ICT context. The first level of research, general NPD research without any limitations of innovation drivers, innovation types, or industry, is too universal for giving the answer to the research question. The third level of research, the literature into success factors for TP projects limited to an ICT context, was conspicuous by our absence, and offered us a clear research gap. Therefore we based all conclusions by way of the second level, the success factor research limited to TP products. 57
The case study provided evidence by supporting 12 out of 13 theoretically defined success factors, and arose three new factors. Based on above, we can summarise following theoretical implications: 1. 2. 3.
4.
We have shown a research gap in success factor research within TP product development in the ICT industry. In this pilot study, we have defined a compact set of success factors in studied discipline consisting 15 defined success factors. We introduced three totally new success factors that previous literature has not found. Scalability, visibility and timing factors arose from our empirical case study. It could be said, that these factors represent a more recent era in the field of NPD research. A pilot type study needs different kind of limitations (e.g. product type (HW/SW), business model) for getting more accuracy conclusions. Therefore the future research is needed (see 5.1.3).
Theoretical implication of this study may help scholars to focus on key issues when studying the success factors of breakthrough development cases. The discussed framework, including 15 TP success factors defined by the literature review and empirical testing, may be a good premise for more detailed future research. The research results of this study are in line with those of the previous literature, but they also complement them by introducing three previously unmentioned [in this context] success factors. The practical implication of the study is that it could help firm management to recognise the real actions needed to reduce [new] product development risks. This benefit is not limited only to the firm level, instead, the particulars benefit the whole industry. This is also very important at a national level, especially at the moment, when we have lots of free resources (e.g. built infrastructure, know-how and a free professional workforce). We elaborate the following practical and managerial implications. The first implication comes from the general level NPD research. The success factors at the NPD level, as far as they depart from TP factors, are good general level guidelines for managing project-oriented organisations. This research recommends that before starting to develop a TP product considering TP success factors, management should ensure that the basics, the NPD level success factors, are taken into account. The NPD level success factors are mostly organisation and process related characteristics. Since the NPD level success factors are not the main 58
focus in our research, we do not elaborate them more. These factors are discussed briefly in Chapter 2.3.1. We secondly observed that the product development process should be the same regardless of the innovation driver (TP or MP). This is even essential, if we want to acknowledge, maybe the most important group of success factors, the market relates. Most of generic product development process models (e.g. Ulrich & Eppinger 2008) positions market related studies to the starting phase of the process presuming management monitoring throughout the process. For achieving successful market entry, the technological ability is not just enough. Therefore, also in the case of TP product development, projects should consider the MP methods, the market related sub-processes. In the area of technology-market matching, customer need identification with customer segmenting and alternative study processes should start right in the beginning of the development project. It is notable, that the alternative study is not just a competitor analysis, but an analysis of direct, indirect and potential solutions. Finally, by means of above, market development actions must start throughout the project. As discussed, because the TP projects are more expensive to implement and they have a higher risk, the time aspect is very critical and it influences on success in many ways. Our third observation is that the management should plan and budget the project from the vantage point of time. This is necessary because the expected adoption time, but also the life time of the TP product is longer [than MP product’s]. The resource planning and ensuring for the development time, and also for the adoption time after that, is a key task for the management. The user-friendly design is perhaps the most effective way to shorten an adoption time. The fourth managerial implication emerged from the case study. The new success factors, scalability, visibility and timing, have not been previously found as a success factors. These characteristics were strongly supported by the industrial informants and they represent modern business thinking. The scalability was seen necessary in consumer products, and a scalable product will solve the problem of many different customers. The visibility factor meant that the early exposure helped to create a phenomenon around the solution and thereby in funding negotiations. It also enables a pre-selling already in development phase. The characteristic of timing was seen, in this context, a technology and product maturity point of view. The technology in use should be ready enough for commercial solutions, but a rough version of the product is enough for market entry.
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Validity We applied the four tests by Yin (2009) for judging the validity and reliability of the study. The four tests, construct validity, internal validity, external validity and reliability, cover few subsections that are called [case study] tactics. Threats to validity are controlled as follows. Construct validity For ensuring construct validity, we applied two tactics: use multiple sources of evidence and establish chain of evidence. In our study we used a holistic multiple-case study design. Yin (2009) distinguished two types of multiple-case studies; holistic and embedded. An embedded study includes more than one embedded unit of analysis inside one particular case, whereas a holistic study concentrates on only one unit of analysis per case. The holistic approach was a natural choice for two reasons. 1) We were interested in the experiences and opinions of the founders of the start-ups (instead of the context of whole organisation). In our TP start-up cases the founder is also an inventor and a soul and the most valuable repository of the firm. 2) In a oneman project4 it is extremely important to find the best sources of information due to resource limitations, however, the multiple-case study method itself meets the requirement of using multiple sources of evidence. The principle of the “establish chain of evidence” tactic is to allow a reader of the study to follow the derivation of any evidence from the initial research question(s) to the case study conclusions and vice versa, from conclusions to research question(s). In the empirical part of the study this was done by archiving all recorded interviews and the transcription documents (the transcription documents were specifically designed for this study). The primary report of the empirical study is Article IV, and according to Yin’s (2009) directions it includes numerous original citations from the interviews. Furthermore, it is possible to track the data collection circumstances (e.g. time and place) as well as the interview questions from the research documentation. In addition to the two tactics discussed, Yin (2009) proposes to let key informants review the draft case study report. We applied this partially by
4 The entire study was implemented outside a research groups without external resources, and by the author only.
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summarising the discussion at the end of the interview, meeting with the informants and agreeing to send both Article IV and the thesis to them for reading after publishing. Internal validity Yin (2009) and Runeson & Höst (2009) highlight that internal validity testing is only concerned with explanatory case studies that have causality (how/why event x leads to event y) aspects. This logic is inapplicable to descriptive or exploratory studies. Since we are describing a phenomenon without causality by applying an exploratory case study (see Chapter 1.2), an internal validity test is not valid in this study. External validity Yin (2009) states that external validity testing is the most problematic task when analysing case study results. External validity defines the domain to which findings of the study are generalisable. Contrary to survey research, which relies on statistical generalisation, case studies rely on analytic generalisation. In analytical generalisation a particular set of the results will be generalised to some broader theory. The multiple-case study is commonly regarded as a more robust method than the classic single case study method (e.g. Herriott & Firestone 1983, Dewayne et al 2004, Yin 2009). Replication logic (replicating findings in two or three other cases) is embedded in multiple-case studies, however, multiple cases (cases selected intentionally) are not generalisable, similar to multiple respondents in surveys (based on sampling logic). In multiple-case studies each case must be selected so that it either predicts similar results (literal replication), or contrasting results (theoretical replication). The researcher defends the external validity of this study by thorough and justified research design (see Chapter 1.2), and in that regard the research method and the case selection was implemented thinking about maximal validity and reliability. The multiple-case study method was carried out with selected cases predicting similar results. Eventually, as discussed previously, we achieved saturation, and the narratives of the informants began to replicate each other. Also, the final number of our units of analyses fulfils Eisenhardt’s (1989) requirement for the theory generalisation. At a general level, as a kind of premise to future research, 61
we trust that the results of the study are generalisable. However, considering the discussed speculations and limitations, further studies (see Chapter 4.1.3) are needed in order to generalise the results further. Reliability The reliability confirms the quality of the research. The objective is to minimise errors and biases and ensure that if some other researcher follows the same procedures with the same studied cases, they should arrive at the same results and conclusions. We see that when requesting (as far as they are not publicly available) and following the research documentation (see construct validity), the other researcher would achieve the same results and conclusions with the same cases. It is notable that replicating the same research procedures with other cases will most probably give different results. In addition to the research documentation, the complete study is divided and reported in individual articles (I-IV), which are published in peer-reviewed required level (JUFO 1) 5 journals, and should be considered when evaluating the reliability of the study, or even replicating it. Incorrect results and conclusions are possible even when investigating as instructed above. The world changes rapidly, and so does the business environment, the firms, even individual people – the informants. The period when the empirical analysis was implemented (2015) must be take into account. Most probably all changed situations in young start-ups and their environments, and grown experience would cause different answers from the informants in future. While this study cannot statistically verify the manner of success factors, however it provides evidence towards complete understanding of this phenomenon. 5.1.2 Future research In future research, we encourage, as previously mentioned, more in-depth success factor study, either with a single case firm [with defined separate success factors], or with a single success factor [with defined separate case firms]. During the research process, we also noticed three variables that should be taken into account in more detailed future studies: the product type (HW/SW), the business model
5 JUFO (Julkaisufoorumi in Finnish). Publication forum, Federation of Finnish Learned Societies, is a classification of publication channels created by Finnish scientific community to support the quality assessment of academic research.
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(B2B, B2C) and the size of the studied case firm. In many (but not all) cases, the responses were similar between hardware firms and also between software firms. The same thing recurred between firms with the same business model and firms of the same size. Some firms defined their product as a platform. The success factors between platforms and stand-alones (see Mäkinen, Seppänen & Ortt 2014) could be a valuable research target. We propose that at least these four characteristics should be distinguished in future research. Furthermore, it would be valuable to determine whether the success factor research is really industry-independent, or if the ICT industry has some industry-dependent characteristics.
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Original publications I
Sarja J (2015) Key factors of successful technology push projects in the ICT context: A review of the literature. International Journal of Information Technology and Management 14(4): 253–273. II Sarja J (2015) Explanatory definitions of the technology push success factors. Journal of Technology Management & Innovation 10(1): 204–214. III Sarja J (2012) A review of the Getting Real software development approach. International Journal of Agile and Extreme Software Development 1(1): 78–94. IV Sarja J, Saukkonen S (2016) Developing technology pushed breakthrough: an empirical study. Journal of Innovation Management. Submitted manuscript.
Reprinted with permission from Inderscience (I, and III) and the Journal of Technology Management & Innovation (II). Original publications are not included in the electronic version of the dissertation.
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Ahmad, Muhammad Ovais (2016) Exploring Kanban in software engineering
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Mustonen, Kaisa-Riikka (2016) Climate change and boreal rivers : Predicting present-day patterns and future changes in hydrological regime and its effects on river communities
684.
Karppinen, Pasi (2016) Studying user experience of health behavior change support systems : A qualitative approach to individuals’ perceptions of web-based interventions
Book orders: Granum: Virtual book store http://granum.uta.fi/granum/
A 685
OULU 2016
UNIVERSITY OF OULU P.O. Box 8000 FI-90014 UNI VERSITY OF OULU FINLAND
U N I V E R S I TAT I S
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UN NIIVVEERRSSIITTAT ATIISS O OU ULLU UEEN NSSIISS U
Jari Sarja
University Lecturer Santeri Palviainen
Postdoctoral research fellow Sanna Taskila
Jari Sarja
Professor Esa Hohtola
DEVELOPING TECHNOLOGY PUSHED BREAKTHROUGHS DEFINING AND ASSESSING SUCCESS FACTORS IN ICT INDUSTRY
Professor Olli Vuolteenaho
University Lecturer Veli-Matti Ulvinen
Director Sinikka Eskelinen
Professor Jari Juga
University Lecturer Anu Soikkeli
Professor Olli Vuolteenaho
Publications Editor Kirsti Nurkkala ISBN 978-952-62-1446-7 (Paperback) ISBN 978-952-62-1447-4 (PDF) ISSN 0355-3191 (Print) ISSN 1796-220X (Online)
UNIVERSITY OF OULU GRADUATE SCHOOL; UNIVERSITY OF OULU, FACULTY OF INFORMATION TECHNOLOGY AND ELECTRICAL ENGINEERING
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SCIENTIAE RERUM RERUM SCIENTIAE NATURALIUM NATURALIUM
