IMM Article summaries
Week 1: Innovation
Article 1.1: Towards a multidisciplinary definition of innovation Anahita Baregheh Bangor University, Bangor, UK Jennifer
Rowley Manchester Metropolitan University, Manchester, UK, and Sally Sambrook Bangor University, Bangor, UK
Abstract
Purpose – This paper aims to undertake a content analysis of extant definitions of “innovation” as a basis for proposing
an integrative definition of organizational “innovation”.
Design/methodology/approach – A literature review was used to generate a representative pool of definitions of
organizational innovation, including definitions from the different disciplinary literatures of economics, innovation and
entrepreneurship, business and management, and technology, science and engineering. A content analysis of these
definitions was conducted in order to surface the key attributes mentioned in the definitions, and to profile the
descriptors used in relation to each attribute.
Findings – The key attributes in the paper present in definitions were identified as: nature of innovation; type of
innovation; stages of innovation, social context; means of innovation; and aim of innovation. These attributes are
defined, descriptors assigned to them, and both a diagrammatic definition and a textual definition of organizational
innovation are proposed.
Originality/value – As a concept that is owned and discussed by many business disciplines, “innovation” has many
different definitions that align with the dominant paradigm of the respective disciplines. Building on these diverse
definitions, this paper proposes a general and integrative definition of organizational “innovation” that encompasses the
different perspectives on, and aspects of, innovation, and captures its essence.
Organizations need to innovate in response to changing customer demands and lifestyles and in order to capitalise on
opportunities offered by technology and changing marketplaces, structures and dynamics. Organizational innovation can
be performed in relation to products, services, operations, processes, and people. Organizations need to innovate in
response to changing customer demands and lifestyles and in order to capitalise on opportunities offered by technology
and changing marketplaces, structures and dynamics. Innovation is recognised to play a central role in creating value
and sustaining competitive advantage. Zairi (1994) and Cooper (1998) have suggested that one of the challenges of
innovation is the lack of a common definition, which undermines understanding of the nature of innovation. In this
paper, our aim is to identify one multi-disciplinary definition of innovation.
Analysis: 60 definitions of innovation were collected from the various disciplinary literatures. A content analysis was
conducted of the collected definitions in order to surface the key attributes mentioned in these definitions considering
the disciplinary variations, and to profile the descriptors used in relation to each attribute.
Findings and discussions:
The attributes are defined as:
1. Nature of innovation refers to the form of innovation as in something new or improved
2. Type of innovation refers to the kind of innovation as in the type of output or the result of innovation
3. Stages of innovation refers to all the steps taken during an innovation process which usually starts from idea
generation and end with commercialization
4. Social context refers to any social entity, system or group of people involved in the innovation process or
environment factors affecting it
5. Means of innovation refers to the necessary resources that need to be in place for innovation
6. Aim of innovation is the overall result that the organizations want to achieve through innovation
In arriving at this final list of attributes two issues have been taken into consideration:
(1) One of the attributes of innovation, which only occurs in three of definition relates to the time of innovation
implementation or adoption in the context of specific industries. Owing to the limited number of definitions
considering the time of innovation, this attribute has been excluded from the definition proposed in this study
(2) Another term which occurs quite frequently is the word “process” which during the content analysis was
replaced by “procedure” for simplification. Usage of this word was an indication of the fact that innovation is a
process not a discrete act.
(3) in defining innovation, scholars have paid more attention to type, means, social context and stages of innovation
and have made relatively limited reference to the aim of innovation. This may potentially be evidence of a
serious disconnection between the rhetoric of innovation and its strategic context. On the other hand, most
research reports and articles on innovation start by explaining the strategic importance of innovation.
On the basis of the key attributes of definitions of innovation and the descriptors used by those definitions to
characterise the attributes, a diagrammatic definition of “innovation” is proposed in Figure 1. The diagram incorporates
the six attributes identified as being common to the various disciplinary definitions of innovation. We do not suggest
that this is the actual or ideal flow, or that the flow is linear. We do not give greater importance to “stages” or “aim” but
simply suggest that these are six common, and therefore important, attributes of innovation.
Definition given from the writers: Innovation is the multi-stage process whereby organizations transform ideas into
new/improved products, service or processes, in order to advance, compete and differentiate themselves successfully in
their marketplace.
Our definition begins with the term “multi stage process” as most of the definition presented earlier have highlighted
that innovation is not a discrete act and is a process.
Secondly, we focus on business organisations in this paper, although we have not explicitly articulated in our textual
definition that innovation can occur in various social entities and contexts.
Third, as shown in the diagram, many definitions have focused on the means of innovation, that is the ways in which
ideas have been transformed into new, improved and changed entities, whether products or services, for example, for
new markets. Therefore, a “multi stage process” together with “transforming ideas into new/improved products ” not
only captures all the stages. . . that different scholars have identified or referred to in their definition of innovation, it
also highlights the fact that ideas are used and transformed (together with other means of innovation) to result in
“New/improved products, services or processes”, the main types of innovation identified together with the level of
change they involve.
Finally, although not often explicitly mentioned in extant definitions, we include the aim of innovation as “successfully
advancing” (referring to process innovations) and “competing and differentiating” to reflect both the overall strategic
aim of innovation and the potentially diverse social and environmental contexts in which innovation occurs. These
diagrammatic and textual definitions, which seek to subsume and supersede earlier definitions with their specific
disciplinary biases, recognize that an all-embracing definition of innovation needs to encompass a number of aspects of
the essence of innovation
Conclusions and recommendations: we have identified how different disciplines view innovation from a different
standpoint and propose distinct definition. The objective in proposing a general definition of innovation has been to
seek to offer a multidisciplinary definition for a multidisciplinary concept. This type of analysis would be useful for
businesses in strategy and planning, and would offer a useful framework for comparing different innovation processes in
different organizations, towards knowledge-building.
However, there are limitations with our paper. As a conceptual paper, we have produced our textual and diagrammatic
definitions drawing on existing theoretical work from a range of business disciplines. In addition, although beyond the
scope of this paper, we have noted there is evidence that the nature and focus of innovation has changed over time.
Therefore, we propose adopting a chronological perspective in future research to explore how meanings of innovation
have evolved, generally and specifically within disciplines.
Article 1.2: Strategic entrepreneurship: Creating competitive advantage through streams of innovation R. Duane Ireland
*, Justin W. Webb
Abstract: In today’s fast-paced competitive environment, firms face the need to be increasingly nimble and adaptive.
While often able to establish a certain level of performance based upon existing technologies, firms are equally as often
to be left flat-footed in the face of emerging, novel technologies. We discuss strategic entrepreneurship as the means
through which firms simultaneously exploit their current competitive advantages while exploring for future
opportunities. Achieving a balance between exploration and exploitation consists of more than merely allocating
resources evenly between the two processes. As discussed, exploration and exploitation are operationally, structurally,
and culturally distinct processes.
Section 1: Managing tension for competitive advantage
Not surprisingly, the challenging nature of competing in a global environment creates several tension-filled questions for
firms: In what markets should we compete? Should we offer standardized products across all markets or should we
modify our products for local preferences? How much risk are we willing to accept to compete in markets with which we
are not deeply familiar? What kinds of skills should we develop in order to become more innovative? The issues raised
by these questions have the potential to create tensions in today’s firms.
What is of interest to us, though, is a particular type of tension that the need to rapidly change creates for firms;
specifically, the need for a firm to learn how to simultaneously exploit today that which it does well relative to rivals,
while also exploring to determine what it needs to do to be successful in the future. This is the tension we consider in
this article. In essence, this tension is between doing what is necessary to exploit today’s competitive advantages and
exploring today for innovations that can be the foundation for the firm’s future competitive advantages.
Our paper proceeds as follows. First, we introduce strategic entrepreneurship as a concept with the potential to
influence the degree of success today’s organizations can achieve while engaging their rivals in competitive exchanges.
We then drill deeper into strategic entrepreneurship by examining its two components: exploration and exploitation.
Explanations of differences in operational activities, organizational structure, and organizational culture that contribute
to effective strategic entrepreneurship are included as parts of these discussions
Section 2: Introducing strategic entrepreneurship
As some of our earlier comments suggest, strategic entrepreneurship (SE) is a term used to capture firms’ efforts to
simultaneously exploit today’s competitive advantages while exploring for the innovations that will be the foundation
for tomorrow’s competitive advantages.
Effective SE helps a firm position itself such that it is capable of properly responding to the types of significant
environmental changes that face many of today’s organizations. Beyond this, and importantly so, effective SE helps the
firm develop relatively sustainable competitive advantages. In addition to being valuable and rare, sustainable
advantages are also difficult for competitors to fully understand, and difficult to imitate as a result of that lack of
understanding (Barney, 1991).
Section 2.1: The challenge of strategic entrepreneurship
Firms find balancing exploration and exploitation to be difficult. Reasons:
First, although exploration contributes to strategic flexibility (a skill through which the firm is able to acquire and
subsequently use information to appropriately respond to change), the outcomes of investments made in the firm’s
exploratory capabilities are uncertain. In general, those working in companies prefer the known to the unknown. (We
can all probably think of individuals for whom this is the case.) Jointly, these factors create a situation in which, in most
firms, exploitation, which takes place by exercising familiar organizational routines, is preferred at the expense of
exploration, which takes place by exercising unfamiliar routines (March, 1991). Some organizational observers label this
a condition in which exploitation tends to drive out exploration.
The fragility of the process used to transition from exploration to exploitation is a second reason companies find
developing an appropriate balance between the two types of actions to be difficult. Indeed, operational, structural, and
cultural changes must take place for a firm to transition from exploring for new opportunities (as well as new ways to
take advantage of them) to exploiting current competitive advantages as the source of today’s competitive success.
Thus, when transitioning, the firm moves from a concentration on diversity with the intent of creating newness (i.e.,
seeking new opportunities, new market space, and new advantages) to a concentration on successfully using current
skills and routines as the source of today’s advantages.
Section 2.2: An expanded view of strategic entrepreneurship
Defining the terms strategy and entrepreneurship is a useful first step in becoming more familiar with the strategic
entrepreneurship.
Strategy is concerned with the firm’s long-term development (Ghemawat, 2002). A firm’s long-term development
includes a number of elements, such as decisions regarding scope, how resources are to be acquired and managed, and
intended sources of competitive advantage, among others.
Entrepreneurship is concerned with actions taken to create newness. We can extend this a bit to note that newness
results from actions framed around efforts to create new organizational units, to establish new organizations, or to
renew existing organizations.
SE results from combining attributes of strategy and entrepreneurship. Here, the firm combines exploration-oriented
attributes with exploitation oriented attributes to develop consistent streams of innovation and to remain
technologically ahead of competitors. Thus, SE is concerned with actions the firm intends to take to exploit the
innovations that result from its efforts to continuously explore for innovation-based opportunities. Effective SE practices
find firms realizing that adapting to change requires an array of newness in the form of innovations.
The stream of newness created through SE results from a balance of actions taken to explore and exploit. Importantly,
this balance positions a firm to take advantage of existing and future opportunities. Exploitation maintains and hopefully
enhances current levels of performance by incrementally extending the firm’s established knowledge base. In doing so,
exploitation also supports the firm’s exploration efforts. Exploration occurs as the firm integrates diverse knowledge
with existing knowledge stocks. Absorbing new knowledge to which the firm gains access while exploring becomes the
foundation for future exploitation actions. Effective SE leads to a combination of both effectiveness and efficiencyoriented forms of newness, and is the source of sustainable competitive advantages.
Although new products highlight to the world a firm’s innovativeness and prestige, some scholars suggest that process
and administrative innovations provide firms with greater competitive advantage than product innovations. The reason
for this is that process and administrative innovations are hidden within the firm. Consequently, it is more difficult for
competitors to reverse engineer and imitate these innovations, as is often easily and quickly achieved with product
innovations.
Section 3: Differentiating exploration and exploitation
In the following sections, we discuss in greater detail the processes of exploration and exploitation. To do this, we
describe the operational, structural, and cultural characteristics enabling efficient and effective SE.
Section 3.1: Exploration: Benefiting from diverse investments
Exploration represents a learning process in which the firm attempts to significantly broaden and deepen its total stock
of knowledge. Knowledge breadth is achieved by seeking diverse knowledge from external sources to add to internal
knowledge. Knowledge depth is achieved as the firm seeks to increase its store of both internal and external knowledge
in focal areas.
As an operational choice, mergers and acquisitions are a path firms use to increase their knowledge diversity. In general,
recent corporate actions suggest that increases in the rate and complexity of environ mental changes find firms seeking
more efficient operational means of exploration (compared to mergers and acquisitions). Strategic alliances and
corporate venture capital programs are examples of means of operating that firms believe are efficient exploration
paths. They also allow a firm to share with other companies the risks and uncertainty associated with exploration
investments.
Exploration and exploitation demand different behaviors—behaviors that are facilitated by a firm’s structure and
culture. Indeed, the structural and cultural mechanisms required to support exploration differ from those needed to
support exploitation.
The degree of centralization of authority, the standardization of procedures, and the formalization of processes are
three structural mechanisms an organization uses to support exploration and exploitation. Centralization of authority
refers to the amount of autonomy individuals have to make decisions regarding the use of organizational resources.
Standardization of procedures refers to the extent to which behaviors are routinized within the firm. The formalization
of processes concerns the degree to which the firm has prepared codified and written instructions about how
procedures are to be followed.
Organizational structures characterized by decentralized authority, semi-standardized procedures, and semi-formalized
processes support exploration.
Decentralization authority patterns yield a large number of occasions throughout a firm for knowledge to be
meaningfully acquired and processed. Decentralization of authority enhances the potential effectiveness of a firm’s
exploration behaviors in that it makes it possible for the firm to examine a relatively large number of potentially
attractive market-related opportunities. In contrast, semi-standardization and semi-formalization contribute to the
firm’s efforts to efficiently use resources when exploring. However, standardization and formalization should not be
used to the point that they stifle the creativity of individuals to whom authority to explore has been decentralized. Thus,
freedom should exist to creatively explore, but within the context of guidelines about when to further pursue a
particular opportunity or not.
Organizational culture supports (the set of values and beliefs that are shared throughout a firm) a company’s structural
characteristics.
Section 3.2: Benefiting from focus
When exploring, firms seek knowledge and resources primarily in order to increase diversity. In contrast, exploitation
finds firms acquiring and bundling complementary knowledge and resources to extend their ability to leverage existing
capabilities and competitive advantages. Firms may tap into external knowledge and resources to achieve several
objectives, including those of increasing the breadth of their distribution channels and the speed at which they
introduce incremental innovations to customers.
Exploitation is also culturally distinct from exploration. The system of shared values supporting exploitation includes a
need for greater certainty regarding tasks and outcomes, a preference for meeting short-term goals, and a commitment
to focus on existing competencies and competitive advantages. Exploitation is based on a heightened level of certainty
regarding market trends. In providing necessary focus, centralization, standardization, and formalization limit the extent
to which experimental behaviors may manifest in exploitation
Section 4: Implications for organizational actions
The decision to engage in SE is a vital but insufficient step to being able to consistently outperform competitors; indeed,
firms reach SE’s potential only by balancing their actions between exploration and exploitation. In slightly different
words, the most successful firms balance the efforts they expend to explore for tomorrow’s opportunities while
exploiting today’s competitive advantages. Firms use three types of mechanisms (operational, structural, and cultural) to
help balance exploration and exploitation; in Tables 1 and 2, we highlight the essence of how this desired balance can be
attained. Achieving this goal is challenging, a reason many firms have yet to accomplish the task. In Table 3, we present
steps firms can take to get started with their efforts to develop an appropriate balance exploration and exploitation
Article 1.3: Cracking Frontier markets
Idea in Brief:
THE CONTEXT: Experts often assume that frontier economies are so underdeveloped that they can’t support consumerfacing businesses—yet hundreds of companies have proved the conventional wisdom wrong with unexpected fast,
sustainable growth.
THE WAY FORWARD: Entrepreneurs who succeed in these markets focus on market-creating innovations: products and
services that speak to unmet local needs, create local jobs, and scale up quickly.
THE SOCIAL GAINS: Frontier markets are often plagued by corruption and held back by poor roads, lack of electricity, and
so on. The essentials of development can be “pulled in” by market-creating innovators—and over time, governments
and financial institutions tend to offer their support.
Market-creating innovations, in particular, provide a strong economic foundation. They share several characteristics.
1. First, they offer many people access to a product or service that was previously unaffordable or otherwise
unattainable— if it existed at all
2. Second, market-creating innovations leverage business models and value chains that focus on profitability
before growth. They often do this by borrowing existing technology and inserting it into a different business
model
3. Third, market-creating innovations are generated by and for a local market—or at the very least, they are
designed with a local market in mind. This means that innovators must do the arduous work of understanding
the ins and outs of that market and making a product simple and affordable enough for it.
4. The increase in wages brings us to the fourth characteristic:
Market-creating innovations generate local jobs, which fuel the local economy. These jobs arise specifically to
serve the local market; they cannot easily be outsourced to other countries
5. Finally, market-creating innovations can be scaled up. In fact, because they make a product simple and
affordable, bringing it within many people’s reach, scaling up is a fundamental part of the process
Corruption
However flawless an organization’s strategy for creating markets in frontier economies, very real barriers exist.
Corruption, the lack of functioning institutions and dilapidated or nonexistent infrastructure constitute formidable
challenges.
Market-creating innovations don’t wait for such obstacles to be removed by resources that are pushed in. They
essentially pull in the necessary resources—creating workarounds or funding the infrastructure and institutions needed
to deliver their products—even if those efforts are not initially supported by the local government.
Market-creating innovations can be a powerful catalyst for improvements to infrastructure and education: Over time,
governments and financial institutions take note of innovators’ efforts and begin supporting the new markets. It may
seem we are suggesting that governments in frontier economies transfer responsibility for infrastructure development
to the private sector. We’re not. We are highlighting the importance of sequencing and the catalytic role of innovation in
infrastructure’s development and improvement
Bringing market-creating innovations to life
How should companies think about creating new markets in frontier economies? We have five guiding principles:
1. Every nation has within it the potential for extraordinary growth
Innovators must first understand that despite what traditional market analysis might. Every nation has within it
the potential for extraordinary growth. Innovators must first understand that despite what traditional market
analysis might tell them, significant opportunities exist in frontier markets. These do not (and should not)
resemble opportunities in developed markets, which differ in their fundamental makeup.
2. Most existing products have the potential to create new growth markets if we make them more affordable
3. A market-creating innovation is more than just a product or a service
It is a system that often generates new infrastructure, regulations, and jobs. A market-creating innovation is
more than just a product or a service. It is a system that often generates new infrastructure, regulations, and
jobs for people who make, distribute, market, sell, and service the offering
4. Obstacles can be mitigated through innovation; innovation does not have to wait for their elimination
The essentials of development and. Obstacles can be mitigated through innovation; innovation doesn’t have to
wait for their elimination. The essentials of development and prosperity can be pulled in by market-creating
innovations, as we have seen. When such innovations take root, infrastructure improves, institutions
strengthen, and corruption is tempered. And once a new market becomes profitable to the various stakeholders
in the economy, including investors, entrepreneurs, customers, and the government, they are often incentivized
to help maintain those resources. The process occurs over time; it is not a single event
5. When innovations target non-consumption, scaling them up becomes inexpensive
Once an opportunity is identified and a business model is. When innovations target non-consumption, scaling
them up becomes inexpensive. Once an opportunity is identified and a business model is conceived to make a
product or service available to a large population of non-consumers, achieving scale is relatively cheap. The first
step is recognizing an area of non-consumption. If you try to exploit existing opportunities in frontier markets—
many of which are already crowded—and hope to get scale up that way, you may find yourself chasing a mirage.
the key to cracking frontier economies lies not in exploiting existing markets, although that may lead to some
success. It lies in creating new markets that serve the billions of non-consumers unable to find a product or
service to help them solve an important problem. The process by which those markets are created, even in the
least likely of circumstances, is what investors and entrepreneurs need to understand. Our research suggests
that this is the critical missing link. Once we focus more effort on that, immense opportunity will ensue, and
inclusive, sustainable development will follow. It is precisely through innovations that generate or connect to
new markets that societies can create jobs, pay taxes, and build their infrastructure and institutions. The quality
that sets market-creating innovators apart—the ability to identify possibilities where there seem to be no
customers—is the reason their work represents such enormous opportunity.
Week 2: Innovation process
Article 2.1: Cooper, R.G. (2019). The drivers of success in new-product development. Industrial Marketing
Management, 76: 36-47.
Abstract: The article identifies success factors from numerous research studies into NPD (new-product
development) performance in industry. Three categories of success drivers have been defined. First, success
drivers, that explain the success of individual new-product projects, are more tactical: They capture the
characteristics of new product projects, such as certain executional best practices (building in voice-of-customer;
doing the front-end homework; and adopting a global orientation for the project), and well as the nature of the
product itself (a compelling value proposition, for example). A second category is drivers of success at the
business level: They include organizational and strategic factors, such as the business's innovation strategy and
how the firm makes its R&D investment decisions; how it organizes for NPD; climate and culture; and leadership
The third category of success divers identified is the systems and methods the firm has in place for managing
NPD.
Introduction: Twenty success drivers have been singled out in this article. For reading convenience, these 20
drivers are arbitrarily divided into three categories (although some drivers cut across categories):
1. Success drivers of individual new product projects: These are tactical and capture the characteristics of the
new-product project or the product itself (see Table 1).
2. Drivers of success for the business, including organizational and strategic factors such as: the business's
innovation strategy and how it makes its R&D investment decisions; climate and culture; leadership; and
how the firm organizes for NPD (see Table 2).
3. The systems and methods that the firm has in place for managing NPD (see Table 3).
1.1
Unique superior products: Delivering differentiated products with unique benefits and a compelling value
proposition for the customer and/or user distinguishes new product winners from losers more often than
any other single factor

are superior to competing products in terms of meeting users' needs, offer unique features not
available in competitive products, or solve a problem the customer has with competitive
products;

feature good value for money for the customer, reduce the customer's total costs (high valuein-use), and boast excellent price/performance characteristics;

provide excellent product quality relative to competitors' products (in terms of how the user
measures quality); and

offer product benefits or attributes that are highly visible and easily perceived as useful by the
customer.
1.2 Voice of the customer: A thorough understanding of customers' needs and wants, the competitive situation,
and the nature of the market, is an essential component of new product success
A market focus should prevail throughout the entire new product project:




Idea generation: The best ideas come from customers. Market-oriented idea generation
activities, such as focus groups and VoC research (ethnography and site visits) to determine
unmet needs or problems, lead to superior ideas (Cooper & Dreher, 2010). Robust ideas also
come from innovative users and web-based customer inputs (open innovation).
Product design: Customer inputs have a vital role in the design of the product, determining the
product's requirements and specifications. Often, market research, when done at all, is done too
late – simply as an after-the-fact check after the product design has already been decided. But
market research must be used as an input to the design decisions, starting with a user needsand-wants study (VoC research).
Before pushing ahead with development: Best performers1 test the product concept with the
customer by presenting a representation of the product – via models, mock-ups, “protocepts,”2
computer-aided design (CAD) drawings, and even virtual prototypes – and gauging the
customer's liking and purchase intent. It's much cheaper to test and learn before development
begins than to develop the product and then begin customer testing.
Throughout the entire project: Customer inputs shouldn't cease at the completion of the predevelopment market studies. Seeking customer inputs and testing concepts or designs with the
user is very much an iterative process. By bringing the customer into the process to view facets
of the product via a series of rapid prototypes-andtests, customer tests of working models, and
field trials, the developer verifies all assumptions about the winning product design.
1.3 Pre-work: Homework is critical to winning. Studies reveal that the steps preceding the actual development
of the product make the difference between winning and losing – the “game is won or lost in the first five
plays.”

Preliminary market assessment – a quick market study to assess market potential and desired
product attributes

preliminary technical assessment – the first technical appraisal of the project, assessing
technical feasibility and identifying technical risks;

detailed market study, market research and VoC research (described above);

detailed technical assessment – in-depth technical appraisal, establishing proof of concept,
intellectual property issues resolution, and an operations or source-of-supply assessment; and

business and financial analysis just before the investment decision to go to full-scale
development.
1.4 Definition: Two of the worst time wasters are project scope creep and unstable product specs. Scope creep
means that the definition of the project constantly changes. Unstable product specs means that the product
definition – product requirements and specifications – keeps changing throughout the Development stage.
Thus, the technical people chase elusive development targets – moving goalposts – and take forever to get
to the goal

Building in a definition step forces more attention on the front-end homework, a key success
driver.

The definition serves as a communication tool: all functional areas have a clear definition of the
product.

This definition provides clear objectives for the development (technical) team members, so they
can move more quickly to their objective.
1.5 Iterations: Spiral or iterative development is the way fast-paced project teams handle the dynamic
information process with fluid, changing information. Spiral development helps the team get the product
definition and product right, in spite of the fact that some information is fluid and even unreliable when the
team moves into the Development stage, particularly in rapidly changing markets. Each iteration consists of:

Build: Build something to show the customer – a representation of the product, such as
computer-generated graphics, a simulation. a virtual-reality prototype, a protocept, a rapid
prototype, a crude working model, an early beta version, a pretotype, or an MVP3 … each
version closer to the final product.

Test: Test each version of the product with the customer.

Feedback: Gather feedback on that version of the product from the customer or user – what
they like (or don't like), and what value they see.

Revise: Reset your thinking about the value proposition, benefits sought, and the product's
design based on the feedback, and move to the next iteration
1.6 Global orientation: multinational firms that take a global approach to new-product development outperform
those that concentrate their R&D spending on their home market. This global orientation translates into
defining the market as international and designing products to meet international requirements, not just
domestic ones. The result is either a global product (one version for the entire world) or a “glocal product”
(one development effort, one basic product or platform, but several product variants of it to satisfy different
international regions). A global orientation also means undertaking VoC research, concept testing, and
product testing in multiple countries rather than just the domestic market, and tailored launch. plans in
multiple countries. It also means employing a global project team with team members in multiple countries
– only one new product project team in five is reported to be a global development team
1.7 Launch: A well integrated and properly targeted launch is the result of a finely tuned marketing plan,
proficiently executed. The launch must be properly resourced in terms of both people and funds. Those who
will execute the launch should be engaged in the development of the market launch plan and therefore
should be members of the project team. This ensures valuable input and insight into the design of the
launch effort, availability of resources when needed, and buy-in by those who must execute the launch –
elements critical to a successful launch.
2.1 Innovation strategy: The ingredients of such a strategy with the strongest positive impact on performance
include:

Clearly defined product innovation goals and objectives

The role of product innovation in achieving the overall businesses goals, to link the product
innovation goals to the business's overall goals.

Strategic arenas defined – areas of strategic focus on which to concentrate new product efforts.
The goal is to select strategic arenas rich with opportunities for innovation

A product roadmap in place, which maps out a series of planned development initiatives over
time, often five to seven years into the future. A roadmap is simply management's view of how
to get to where they want to be or to achieve their desired objective
2.2 Focus: Smart firms have built in “tough gates with teeth” (Cooper, 2009). The result is better focus: fewer
but better development initiatives.
2.3 Leveraging core competencies: Synergy/Leveraging means having a strong fit between the needs of the new
product project and the resources, competencies, and experience of the firm in terms of:

R&D or technology resources (ideally the new product should leverage the business's existing
technology competencies);

marketing, sales force and distribution (channel) resources;

branding, image and marketing communications and promotional assets;

manufacturing, operations or source-of-supply capabilities and resources;

technical support and customer service resources; and

management capabilities. These six synergy or leverage ingredients become important checklist
items in a scoring model to prioritize new product projects
2.4 Targeting attractive markets: New products targeted at more attractive markets are more successful). Thus,
market attractiveness should be considered in project selection and scoring models. There are two
dimensions to market attractiveness:

Market potential: Positive market environments, namely, large and growing markets with large
long-term potential and where the purchase is important to the customer.

Competitive situation: Negative markets characterized by intense price competition and low
margins and competitors with strong products, capable competitive sales forces, channel
systems, and support service.
2.5 Resources available: Best-practice companies commit the necessary resources to new products, much more
so than most firms
2.6 Teams: the way the project team is organized and functions strongly influences project outcomes
2.7 Climate: A positive climate for innovation is one of the top three success factors that distinguishes topperforming businesses in new product development, with a huge impact on performance results.
2.8 Leadership: In best-performing businesses, senior management makes a long-term commitment to product
innovation as a source of growth. It develops a vision, objectives, and a strategy for product innovation. It
makes available the necessary resources for product development and ensures that they aren't diverted to
more immediate needs in times of shortage
3.1 Gating systems: Stage-Gate systems are simply roadmaps or “playbooks” for successfully and efficiently
driving new products from idea to launch. The goal of a robust idea-to-launch system is to integrate the best
practices outlined above into a single model. These gates are the quality control checkpoints in the system:
At each gate, the project team meets with senior management, the gatekeepers, to seek approval and
resources for their project for the next stage. The gates thus open the door for the project to proceed and
commit the necessary resources – people and funds – to the project team.
3.2 Accelerating development: Speed offers the competitive advantage of being first on the market, namely
“first mover advantage”. Speed means less likelihood that the market situation has changed. And speed
results in a quicker realization of profits. Therefore, the goal of reducing the development cycle time is
admirable
3.3 Agile: Agile software development is a group of software development methodologies based on iterative
and incremental development, where requirements and software solutions evolve through collaboration
between self-organizing, cross-functional teams. Agile promotes adaptive planning, evolutionary
development and delivery; utilizes a time-boxed iterative approach; and encourages rapid and flexible
response to change
3.4 Generating breakthrough ideas: Great ideas are the foundation for great new products. Many commercially
important products are initially thought of and even prototyped by users rather than by suppliers. Such
products tend to be developed by “lead users” – innovative companies, organizations, or individuals that are
well ahead of market trends and even have needs that go far beyond the average user
3.5 Execution: “Do it right the first time” is an old adage, referring to the fact that poor quality-of-execution
usually results in much waste by having to go back to fix things. Quality can be built into any process,
whether it is a manufacturing process or an innovation process, and top firms promote quality of execution
in new-product projects: a project team with capable and trained people; dedicated team members with
time available to do a quality job; management mentoring and support; a clear innovation process with
useful guidelines for the project team; and quality checks or “gates” during the project that ask “are we
doing this project right?”
Article 2.2: Salerno, M.S., L.A. de Vasconcelos Gomes, D.O. da Silva, R.B. Bagno and S.L.T.U. Freitas (2015).
Innovation processes: Which process for which project? Technovation, 35: 59-70.
Abstract: The innovation process has traditionally been understood as a predefined sequence of phases: idea
generation, selection, development, and launch/diffusion/sales. Drawing upon contingency theory, we argue
that innovation process may follow a number of different paths. Our research focuses on a clear theoretical and
managerial question, i.e., how does a firm organize and plan resource allocation for those innovation processes
that do not easily fit into traditional models. This question, in turn, leads to our research question: Which
configuration of innovation processes and resource allocation should be employed in a given situation, and what
is the rationale behind the choice?
Introduction: Which innovation processes best fit different types of projects? More specifically, what would be a
typology of innovation processes, and what would be the rationale for each type of process? To respond to our
research question, we incorporate the contingency theory proposed by Lawrence and Lorsch (1967) and
Thompson (1967)—with roots in Woodward (1965)—as the anchor for our scientific inquiry. This theory holds
that the way to organize a business depends on the nature of the environment in which the organization is
situated. We interpret the contingency approach as a way to cope with uncertainty; in classical terms, this
primarily indicates technological and market uncertainties.
Literature review: Traditional models for managing innovation have focused on new product development (NPD)
activities. Developing products involves engaging in a bundle of activities, including managing and transforming
resources, gathering information and expertise on specifications and creating products that meet (or create)
market demand
Goffin and Mitchell (2010) proposed the Pentathlon framework, a five-dimensional model for innovation
management. Hansen and Birkinshaw (2007) proposed the idea of the innovation value chain, in which the NDP
is an important activity, but there are other equally important activities before it, parallel to it and after it, such
as idea generation, selection/conversion, and diffusion. Moreover, Hansen and Birkinshaw (2007) sought a
degree of integration among traditionally isolated approaches and proposed organizational forms that enable
teams and middle managers to develop ideas and even build prototypes without prior authorization by a board
or committee.
The purpose of this research is to identify new configurations of innovation processes other than the traditional
one (largely recognized by the literature) and the rationale of each type of process. The research aims to
develop the theory of innovation processes.
Main findings and discussion – which process for which innovation project?
Eight types of innovation process:
1. Traditional process: from idea to launch
The most common process is the traditional model (Fig. 1). This process is more common in large companies
that mass-produce for inventory; sales occur after production. The traditional process is typical for frequent
incremental innovations that consume a reasonable time and resources; by frequent and reasonable, we
mean a number of projects and an amount of time and money that justifies a managerial system dedicated
to the projects. The traditional process is typically used by companies with a well-structured innovation
process: on the one hand, it makes incremental innovation easier; on the other hand, it inhibits radical
innovations, particularly those related to a market that is forming, as opposed to a mature or a nonexistent
market. This traditional process addresses uncertainties sequentially. The main contingencies that appeared
to be associated with this process are a medium–long product life cycle, a mature market, mature
technologies, medium–high expenditures in R&D and engineering (RD&E), product improvement, product
development, and production for inventory (not for order). The level of resources involved partially explains
the formality of the process.
2. Anticipating sales: tailor-made approach (open order)
A good metaphor to illustrate the second process is the production of tailor-made costumes. Sales occur
prior to development and production. The relationship with the client is the main contingency and
sometimes includes a large service component. In these situations, the innovation idea is jointly constructed
with the client; only after this joint construction is the project formalized. Although some resources are
allocated during initial negotiations, once the order is formalized, an important level of human and financial
resources is allocated to product development. The client finances the development of product and process.
The delivery of the product ends the process. Uncertainties: to the idea construction with the client, to the
company’s capability of developing the product. The main contingency linked to this process is the role of
the client
3. Anticipating sales from a given client specification (closed order)
As opposed to the previous process, the client in process 3 has a predefined specification (e.g., functional
requisites or form) that the order must fit. For the vendor, this process contains neither idea
predevelopment nor a maturation period for the specifications. For the firm, the selection phase involves a
decision about whether to develop the product. By contrast with process 2 (the anticipating sales: the tailormade approach), there is no uncertainty linked to idea construction with process 3. The other arguments
regarding uncertainties and contingencies are similar to those discussed above for process 2
4. Started by a public or private call
This process is typically associated with public requests for contract and for projects funded by resources
from official agencies that are linked to public procurement for innovation as part of mission-oriented
innovation policy; however, it is also found in private contract bids, e.g., when a systems integrator launches
a request for bids. The call usually defines the functional requirements of the product to be developed. The
flow begins with predevelopment, which consists of preparing an initial analysis of the feasibility of the
project for the company. Companies therefore have a trade-off: better preparation for the call results in a
better chance of winning it but also in higher expenditures before the contract. The main factor that
explains this process is the call. From the point of view of the developer, we can interpret the call as a way
to reduce market uncertainties by anticipating sales. Thus, the main activities of the innovation process
occur after the sale, that is, after winning the call. In that sense, the cases analyzed show the positive effects
of public procurement policy on improving innovation. By analogy, we could consider the main contingency
to be the position of the client in the process, which is similar to the develop-to-order processes (processes
2 and 3).
5. Process with a stoppage: waiting for the market
The cause of the stoppage is as important as the stoppage itself for conceptualization and managerial action.
Process 5 (with a stoppage: waiting for the market) conducts innovation efforts similarly to the traditional
process from idea to launch until an uncertainty related to the market causes a temporary halt or pause
after initial sales. The stoppage occurs after the selection and initial development of the idea. Thus, the flow
of this innovation process can be divided into two segments. The first segment concerns idea generation,
idea selection, development, and initial diffusion/sales. In the first segment, the product is developed to
pilot or experimental plant scale. Diffusion (sales) is performed for a specific market niche, i.e., the lead
users. There is a stoppage in the process because the perceived market is not large enough to justify further
development, whether in production processes, product specification, or production facilities. While the
process is halted, the company allocates resources to enlarge or create the market. With perceived market
expansion, by sales contracts or otherwise, the company returns to the second segment of trying to achieve
an industrial and commercial scale of production. Thus, the stoppage represents active behaviour: the
development activity is interrupted, but the project is not abandoned because the company directs its
efforts to “create” a market. A first diffusion stage (the initial sales) then occurs under the preliminary
product and/or process specifications. During the initial sales, the company determines that there is a great
uncertainty in the growth of demand. This uncertainty leads to a stoppage in the development efforts until
the market variables are better understood. Based on this learning, a second development stage is
performed, followed also by a second diffusion stage
6. Process with a stoppage: waiting for the advance of technology
This process is similar to the previous one, but the stoppage in this process is caused by a technological
bottleneck within the product or process development. The first phase of the process contains the idea
generation, the selection, the initial development, and the initial diffusion. When the technological
bottleneck is surpassed, the final development of the product begins, and diffusion/sales close the process.
Therefore, we separated the process stoppage: waiting for technology (process 6) from the process
stoppage: waiting for market (process 5). The main contingency associated with this process is technological
trajectory.
7. Process with stoppage: waiting for the market and for the advance of technology
Stoppages. There is a first stoppage because of technological issues and a subsequent stoppage to (actively)
wait for market viability. Some companies launch an initial, and sometimes primitive, version of the product
to be the first to market or to establish an initial position in the market. The first phase of the process
ensues until the preliminary diffusion. Before continuing development, the company continues to search for
new clients and markets. Development accelerates which improves the product and reinforces sales efforts.
In this process, there is a combination of the market and technology contingencies that were explained in
the previous two processes
8. Process with parallel activities
We observed cases in which the diffusion/sales phase starts before the end of product development (Fig. 7).
The development continues until a first version or a sample of the product is obtained. There is a version of
the product available that enables the company to begin diffusion, which is performed in parallel with the
remaining development efforts.
Conclusion: The literature on innovation project management models has been dominated by the one-size-fitsall approach for modelling and interpreting the innovation process. This approach tends to ignore important
contingencies related to real innovation projects. We have addressed our research based on the following
research question: Which configuration of innovation processes is appropriate for which situations, and what is
the rationale behind this choice?
Article 2.3: Cooper, R.G. (2021). Accelerating innovation: Some lessons from the pandemic. Journal of Product
Innovation Management, 38(2): 221-232.
Abstract: Five approaches to accelerated development are outlined here: The first two deal with adequately
resourcing new-product projects, namely the use of focused teams; and effective portfolio management to
prioritize projects and reallocate resources. Newer digital tools are outlined that speed new-products
developments. Finally, two development methods are described that move development projects faster: Lean
development and Agile development. Accelerated development also has hidden costs: undertaking less
innovative projects and cutting too many corners. Although important, the topic is under-researched, and the
limited research has yielded inconclusive results about acceleration's expected benefits.
Practitioner Points:
• The Pandemic has focused the spotlight on the need for accelerated product innovation, and also revealed
ways to get to market faster that are generally applicable.
• Focused project teams coupled with effective portfolio management – fewer projects but better projects –
increases resources on projects to maximize speed.
• New digital tools – from Virtual Reality to AI – can both enhance and accelerate new-product projects.
• Lean Development removes waste and inefficiencies in the idea-to-launch process through value stream
mapping.
• Managers should also overlap stages in their new-product process and move key decision points forward to
minimized the impact of long lead-time tasks.
• Agile methods borrowed from the software world can be built into more traditional gating processes to yield
increased productivity and faster development times.
How to accelerate NPD: The need is to re-think the firm's innovation process and methods—moving to new
approaches and a re-designed process. Here, are five practices that can be built into a new or re-invented
innovation process in order to get new products to market faster.
Focused project teams: The most frequently cited challenge in new-product portfolio management is too many
development projects in the pipeline. The result is that people resources are spread too thinly across too many
projects, so that every project, even the important ones are under-resourced.
Benchmarking studies show that top-performing businesses are considerably more focused than others, with
dedicated resources for product innovation: Half the top businesses use dedicated teams for projects, and more
than half have fully dedicated product-innovation groups that only work on new products
Prioritizing projects at regular portfolio reviews: At these reviews, senior management goes through the list of
active development projects, checks that there is the right mix and balance, but most important, does a forced
ranking of projects:1 to N. The goal is to do fewer projects but better projects, resource them properly, and get
them done!
The Productivity Index is an effective way to prioritize projects when there are constrained resources, which is
usually the case.
Digital tools to accelerate knowledge generation: Numerous digital tools are available to accelerate the productdevelopment process. Newer technologies have made prototype development easier, faster, and less expensive.
Lean development: Many firms’ new-product processes have become bureaucratic and slow. Value stream
analysis is a well-known Lean-Six-Sigma methodology, designed to remove waste and inefficiencies from
business processes; it has seen widespread success in factory-floor settings. But the Lean method can also be
applied to new-product development, specifically to remove waste and to make the idea-to-launch system more
efficient. Re-designing the process to overlap tasks, namely parallel processing— starting one task or stage
before the preceding one is 100% complete—can save time too.
Agile development: Agile Development methods were developed in the 1990s in the software world to deal with
projects facing uncertain and changing information. Agile is incremental and iterative, a series of build-testandrevise iterations; it is adaptive and evolutionary—the product definition and project plan change as the project
moves forward; it emphasizes frequent and fast delivery of results (e.g., product versions), in rhythmic takt time;
and it is based on self-managed project teams.
Agile (the Scrum method, the most popular) works like this for software development: Agile breaks the
development process into a series of short, iterative, and incremental timeboxed sprints, each typically about 2
weeks long. At the beginning of each sprint, the development team holds a sprint planning meeting to agree on
sprint goals and create a task plan for the sprint. Once the sprint is underway, the team meets every morning—
their daily stand-ups or scrums—to ensure that work is on course, share information, and solve problems. At the
end of each sprint, software increments, potentially releasable, are demonstrated to stakeholders, both
management and customers. Finally, the team meets in a retrospective meeting to review how they can
improve the way they work and execute the next sprint better. The team then plans the next sprint based on
customer and management feedback.
This new Agile-Stage Gate approach yields three important positive results for manufacturers (Cooper & Fürst,
2020a):
1. Development is faster: Sprints are time-boxed—a hard stop; the team is focused, and partially or fully
dedicated; and frequent scums resolve problems immediately. The result is higher productivity, closer
adherence to the time schedule, and shorter development cycles.
2. Gets the product right: Product designs (features, functionality, etc.) are validated by customers (and
management) as the project moves along—early, often and cheaply.
3. Team morale is higher: The team is self-managed, self-organizing, ideally co-located, and has decision
authority.
Acceleration is not a panacea: There has never been a consistent set of research results to support the argument
that “first in wins.” Often the first to get to market does better, but not always; sometimes the “second in”
learns from the mistakes of the pioneer, and does better.
Some research on accelerated development looked at more easily measured dependent variables, such as the
impact of speed on development costs; these studies often yield negative results. While “development cost” is
more reliably measured, it may not be a valid metric, however: One usually moves quickly not to save money,
but in order to gain competitive advantage and market share.
Measuring cycle time: Another study found shorter cycle time was correlated with an increase in the new
product's sales when it is managed across all of the stages of the process. Cycle time reduction may also yield
major negatives (Crawford, 1992). In order to cut cycle time, a firm may avoid bolder innovations, which often
involve learning and experimentation and thus take longer; the firm may instead focus on smaller, less
challenging projects. A second major negative is cutting corners and making mistakes—cutting short key
activities such as VoC or front-end homework. Project teams, driven by time, may also become too committed
to their project and its plan, and fail to pivot when needed. Finally, high priority projects tend to chew up a lot of
resources—pulling team members from other important duties to focus on the one project.
Conclusion: Accelerated innovation is a worthy goal in product development, and has the potential for delivering
many benefits, as witnessed in developments during the pandemic. Five approaches to accelerated innovation
have been outlined —from better focus and portfolio management through to Agile and Lean development.
Many unanswered questions remain however, and thus accelerated innovation is a fertile field for academics to
investigate. Three closely related research questions are:
1. Does accelerated innovation really work—does it yield benefits, specifically which benefits and how much?
2. What are the hidden costs of accelerated innovation?
3. Which proposed methods work the best, why, and under which conditions?
One reason for the inconclusive results regarding the benefits of accelerated innovation is the unreliable and
often invalid metrics that try to capture the benefits of speed to market.
A fourth research question focuses on the implementation of acceleration methods. Agile methods were first
implemented in the software world; but developing a physical product is much different: it's difficult to do
demos on-line to customers; and it's expensive to pivot and change a product's design near the end of
development. Thus manufacturers have been forced to make significant modifications to the Agile approach.
But more research is required here, not just for Agile, but for the other acceleration methods too. Only then will
we have the knowledge, confidence, and motivation to move forward with accelerated innovation.
Week 3: Innovation success and failure
Article 3.1: Von Zedtwitz, M., S. Corsi, P.V. Søberg and R. Frega (2015). A typology of reverse innovation. Journal
of Product Innovation Management, 32(1): 12-28.
Abstract: Reverse innovation commonly refers to an innovation initially launched in a developing country and
later introduced to an advanced country. This study expands the espoused definition of reverse innovation
beyond its market-introduction focus with reversals in the flow of innovation in the ideation and product
development phases. Recognizing that each phase can take place in different geographical locations, the paper
then introduces a typology of global innovation with 16 different types of innovation flows between advanced
and emerging countries, 10 of which are reverse innovation flows. The latter are further differentiated into weak
and strong reverse innovation, depending on the number of innovation phases taking place in an emerging
country. The study addresses questions of ethnocentrism and the continuity of the flow of innovation, and
discusses possible extensions of the model with respect to the number of geographical categories and phases of
innovation. Four research propositions highlight areas for future investigation, especially in the context of
optimizing a firm’s portfolio of global innovation competence and capability. The implications for management
are concerned with internal and external resistance to reverse innovation. Most significantly, while greater
recognition and power of innovation in formerly subordinate organizational units is inconvenient to some, the
ability to leverage the potential of reverse innovation makes a firm more likely to succeed in global innovation
overall.
Introduction: According to the traditional view, new products and technologies are first developed and launched
in advanced countries, and only later introduced and commercialized in less developed countries when they
have become increasingly mature, out-of-date, and obsolete. Recent examples of products first introduced in
developing countries and only later in advanced countries have challenged this paradigm. The term “reverse
innovation” has become popular in both academic and managerial discussions to describe innovations as
emanating from developing rather than advanced countries. Immelt, Govindarajan, and Trimble (2009), for
instance, described reverse innovation as the opposite of the “glocalization” process, in which multinationals
first make products at home for the home market and subsequently localize them to other, usually less
sophisticated markets.
Arguing that market-oriented definitions are incomplete because they do not include the loci of idea generation
and development as determinants of reverse innovation, we extend and refine them by defining reverse
innovation as any type of global innovation that, at some stage, is characterized by a reversal of the flow of
innovation from a developing to an advanced country, as long as this innovation is eventually introduced to an
advanced country’s market. The main conceptual goal of this paper is to propose a comprehensive global
innovation model that emphasizes the spatial patterns of innovation flow. Based on the linear model of the
innovation process (e.g., Godin, 2006), it clarifies and expands the notion of reverse innovation beyond a purely
market-introduction concept by identifying two additional reversals in the flow of innovation: developmentbased and ideation-based reverse innovation
The shifting locus of innovation:
Vernon’s product life-cycle hypothesis: the location of these innovation activities is in advanced countries not
only because the entrepreneur has access to scientific knowledge and technology, but also because he has a
greater likelihood and incentive to apply this knowledge, as he is geographically colocated with potential
consumers.
Cantwell (1995): the product life cycle may start in any advanced country leading the given technological
discipline. The actual development of an original idea into a product and its manufacturing is now located
wherever a company has a center of advanced know-how and production.
Why has global innovation activity changed?
Foreign R&D is gaining a foothold in developing countries, even though R&D in advanced countries still
dominates the global innovation footprint. Also, tracking the locus of patenting is another measure used to
quantify the shift of global innovation activity. Developing countries have more than doubled their share of
global patent applications.
Why did global R&D organization emerged? (four departures from Vernon’s premises regarding the global flow
of innovation as captured in the product life cycle constitute the ingredients for what management practice and
the literature call “reverse innovation.”)
 companies no longer target their home country as their default primary market. MNCs from smaller
countries have long abandoned this practice by aiming first at large advanced markets
 product development and R&D are not carried out exclusively in advanced countries but increasingly
conducted directly in developing countries to benefit from local factor conditions and enhance
innovation for local markets
 products developed in and for developing countries occasionally prove superior to competing products
elsewhere
 entrepreneurs and firms in developing countries not only develop but also conceive product ideas based
on their own technologies and scientific insights.
A global model of reverse innovation:
Definitions of reverse innovation along the flow of innovation:
1. development-based interpretation of reverse innovation, we emphasize the fact that innovation may flow
across different locations.
2. ideation-based definition of reversal of innovation denotes the creation of the original idea or concept in a
developing country and its subsequent transfer to an advanced country where this concept is implemented
further
Stages of innovation process:
1. Idea generation: This early stage is characterized by tacit and often sticky knowledge, which makes spatial
transfers costly and time intensive.
2. Development: Transforming the concept into a finalized product. Includes prototyping, performance tests,
industrialization of the new product
3. Primary market introduction
4. Secondary market introduction
A model for global innovation flows: by denoting advanced or developed countries with “A” and developing countries
with “D,” we arrive at a binary tree of 16 possible global flows of innovation. This “map of global innovation flows” (see
Figure 1, Table 3) also depicts reverse innovation as a subset of global innovation flows.
Ideation/concept development, new product development, and first market introduction are key innovation phases;
secondary market introduction is not. As a further refinement, we thus define reverse innovation in the strong sense as
a reverse innovation that has at least two of its key innovation phases taking place in a developing country. This
definition contrasts with a reverse innovation in the weak sense, which has only one of its key innovation phases taking
place in a developing country.
Reverse innovations in the strong sense are originating mostly from developing countries, according to the model, while
weak reverse innovation originates from advanced countries
In the future, there will be more reverse innovation (both weak and strong) from developing countries with improved
institutional frameworks.
Managerial implications:
 Resistance from headquarters and key R&D departments when their authority to lead global innovation projects
is undermined, resistance from engineers who distrust defeatured products to meet their high standards of
technical sophistication, and resistance from customers and markets who are reluctant to adopt products
pioneered outside their own advanced home countries because of perceived quality and reliability issues
 These principal-agency issues, including not-inventedhere resistance within central R&D labs and the
operational difficulties of overcoming inefficiencies in distributed R&D work

At the level of the process of innovation, companies prefer to keep concept development and product
development colocated. The advantage of implementing product development in a low-cost location is often
more than counterbalanced by the costs of moving tacit knowledge around, or the inefficiencies of multisite
collaboration and coordination
Article 3.2: Anthony, S.D., P. Cobban, R. Nair and N. Painchaud (2019). Breaking down the barriers to innovation.
Harvard Business Review, 97(6): 92-101.
Introduction: Executives are dissatisfied with their firms’ innovation performance. Across industries, one survey after
another has found the same thing: Businesses just aren’t getting the impact they want, despite all their spending. Why?
We believe that it’s because they’ve failed to address a huge underlying obstacle: the day-to-day routines and rituals
that stifle innovation. Fortunately, it’s possible to “hack” this problem. Like most hacks, our approach isn’t expensive,
though it does take time and energy. It involves setting up interventions we call BEANs, shorthand for behavior enablers,
artifacts, and nudges. Behavior enablers are tools or processes that make it easier for people to do something different.
In this article we’ll describe a variety of BEANs that firms have used to unleash innovation, the characteristics that make
them effective, and how your organization can develop and implement its own BEANs. But first we’ll briefly examine the
behaviors that drive innovation and the barriers that thwart it.
Innovation behaviours and blockers: To us, innovation doesn’t mean mere inventiveness. In our work we define it as
“something different that creates value.”
In our work and research, we’ve found that the most innovative organizations exhibit five key behaviors:
1. They always assume there’s a better way to do things.
2. They focus on deeply understanding customers’ stated and unstated needs and desires.
3. They collaborate across and beyond the organization, actively cross-pollinating.
4. They recognize that success requires experimentation, rapid iteration, and frequent failure.
5. Last, they empower people to take considered risks, voice dissenting opinions, and seek needed resources.
Barriers of innovation:
1. Lack of time
2. Increased costs
3. Lack of infrastructure for implementing ideas
4. Organizational inertia
The keys to effective BEANs: We determined that successful BEANs typically are:
1. Simple. Interventions that are easy to adopt and remember gain traction much more quickly.
2. Fun. When an activity is engaging and social, it’s intrinsically rewarding, which makes people more likely to do
it— something the science of motivation has long recognized.
3. Trackable. The ability to monitor performance and compare it against that of others is a powerful motivator.
(This is why activity trackers like Fitbit have helped many develop better exercise habits.) So it’s critical for
BEANs to include a mechanism for measuring their results.
4. Practical. The best BEANs are smoothly integrated into existing meetings and processes and don’t require major
changes or entirely new routines.
5. Reinforced. People often need physical and digital reminders to keep using the new habits.
6. Organizationally consistent. One of the most cited papers in the change literature is Steven Kerr’s 1995 classic
“On the Folly of Rewarding A, While Hoping for B.” Effective BEANs don’t encourage people to do one thing if
the company punishes them for that behaviour or rewards them for something else.
How to build a BEAN: We’ve created a three-step process companies can use to develop them.
1. Specify the desired characteristics. First the team outlined what kind of organizational traits it wanted,
describing a culture that would be agile, learning-oriented, customer-obsessed, data-driven, and experimental.
It then listed behaviors under each of them
2. Identify blockers. Next the team looked for things that were getting in the way of the innovative behaviors.
3. Come up with interventions. Last the culture team designed ways to eliminate the blockers. Here are three
interventions that were created to tackle lack of context, voice, and time at the center:
a. Lack of context. This blocker reinforced employees’ sense that their business-as-usual approach was
good enough. The BEAN called “culture canvas” helps them gain a clearer sense of expectations,
organizational context, and who does what. Giving teams clarity about their goals and the scope to push
boundaries further empowers their entrepreneurial spirit
b. Lack of voice. A BEAN called “team temp” was devised to liberate employees to speak up when they
saw problems. This quickly reveals if the team has an and prompts a discussion—led by the team
leader—about what’s going on and how it can be addressed.
c. Lack of time. To bust this blocker, the culture team created the “70:20:10” BEAN. It gives software
developers explicit permission to spend 70% of their time on day-to-day work, 20% on workimprovement ideas, and 10% on experiments and pet projects. By formally freeing up chunks of time for
unspecified experimentation, 70:20:10 encourages innovative thinking. To reinforce it, the culture team
also created a ritual in which developers shared the learnings of their experimental projects with one
another.
Article 3.3: Raajpoot, N. and A. Sharma (2021). The function of innovation culture in the success of new services. Journal
of Global Scholars of Marketing Science, 31(3): 392-414.
Abstract: The role of culture has been important for the success of new service development. There has been extensive
research in the area of new service development, but an area that needs additional research is innovation culture. Using
data from 96 companies in 24 countries, we first identify important global service success factors: innovation culture,
global orientation, incentives and rewards, collaboration with external partners, market analysis, and identifying
customer needs. We then test a model between the success factors and the success of new services and find that
innovation culture is critical in the success of new services. We also find that collaboration is the most salient factor in
success. In the absence of innovation culture, understanding customer needs does not improve success chances, and
financial rewards help develop an innovation culture.
Introduction: The issues are particularly severe in new service development. The intangible nature of services, the less
structure of new service development, and the difficulty in designing optimal services make new services difficult to
develop, build, test (prototypes), and launch.
Extant research has examined the factors that affect the success of new services, but there is a gap in the literature on
establishing the relationship between success factor variables. Our focus is on developing a comprehensive model to
understand new service development and examine both direct and indirect effects of the selected success factors and
new service success
Developing a model of success factors: We focus on the relationship between innovation culture, global orientation,
incentives/rewards, collaboration, customer needs, and market analysis, and new services success. The constructs that
reflect organizational characteristics are innovation culture, rewards and incentives, and global orientation. For strategy,
the construct is collaboration with external partners, and for marketplace, the construct is marketing analysis and needs.
1. Innovation culture: Innovation culture refers to a set of shared assumptions, values, beliefs, attitudes, and
behaviors of organizational members that could facilitate the creation and development of new products,
services, or process innovation. The culture necessary to create something novel and valuable would require an:
intent to innovate, an infrastructure (technical, financial, and processes), and a well-developed strategy to
enable appropriate behaviors (marketing orientation, etc.). Innovative cultures encourage risktaking and avoid
punishment when new products or services fail to achieve desired results. The innovation capabilities of an
organization depend not only on what exists within the organization but also on the society that is external to
the organization
2. Rewards and incentives: They keep members of global service development teams motivated. An effective
reward system encourages people to take share knowledge, engage in problem-solving and take prudent risks to
develop successful innovations
3. Global orientation: Global orientation views the world as a single marketplace, while acknowledging
geographical or administrative boundaries. A global orientation helps companies develop global marketing
programs with appropriate cultural-difference adjustments, making way for greater efficiencies in production,
faster deployment times, and better financial performance. Understanding a global market with its intricacies
allows firms to better understand their global customer needs, enhancing innovation culture.
4. Collaboration with external partners: Innovation is complex and it needs a lot of resources and expertise. That
is why firms look for external collaborators to overcome the deficiencies in resources and knowledge and exploit
synergies based on the complementary strength and expertise that exist in partnering organizations.
5. Marketing analysis and customer needs: Market orientation refers to a prevailing culture in the organization
that is focused on conducting its business from a customers’ perspective by developing processes, such as
customer linking, market sensing, competitor sensing, and customer service. Market orientation primarily aims
at the generation and dissemination of proper market intelligence, providing the firm with a knowledge
advantage, which leads to more relevant and superior services that better meet market circumstances. A
thorough understanding of customer needs helps companies develop successful new products and services and
produce better results when firms have acquired marketing analysis capabilities
Discussion:
 Monetary incentives contribute positively to innovation. It may be argued that the motivation for radical
innovation is primarily intrinsic, but this research suggests that the presence of extrinsic rewards, in combination
with intrinsic rewards, will not inhibit innovation.
 Incentives and rewards influence success indirectly. Rewards load significantly on innovation culture, which in
turn loads significantly on the success of new services
 Our study shows that collaboration with external partners is the most important success predictor
 Knowing customer needs alone does not predict success. Knowing customer needs, however, contributes
significantly to developing an innovation culture, and an innovation culture does directly contribute to the
prediction of success. Knowing consumer needs aids in creating an appropriate infrastructure to address those
needs is the other half.
 Standard market analysis practices reinforce the innovation culture–marketing competencies can be used to
implement the intended innovations.
Week 4 Customer value and business models
Article 4.1: Payne, A., P. Frow, L. Steinhoff and A. Eggert (2020). Towards a comprehensive framework of value
proposition development: From strategy to implementation. Industrial Marketing Management, 87: 244-255.
Abstract: Value propositions (VPs) can play a major role for the strategy development and implementation
process in B2B markets. This article re-assesses the VP in the context of both strategy and implementation. A
new conceptual framework for addressing VP design and development is offered, which incorporates five key
interrelated phases of implementation that need to be comprehensively addressed. This research provides a
theoretically sound and practically applicable VP development framework, integrating the firm's strategic
considerations, ensuring a fit between its business model and customers' needs, and reflecting the nature of
B2B markets through its dynamic perspective. In addressing key implementation issues, the article provides
firms with a robust approach to addressing the dynamic competitive environment, as well as taking into account
changing customer needs.
Introduction: The proposition concept was principally concerned with business-to-consumer (B2C) products and
only more recently was applied to the context of business-to-business (B2B) markets. The VP concept has
potential as the firm’s most important single organization principle, crucial to the value creation process, the
essence of marketing strategy, a statement of the firm’s core strategy with decisions impacting implementation
of marketing right across the firm.
VP concept is a tool for communication the value a business offers to customers, and at the same time is
answers the question of how the business will make the value actually happen for the customer, highlighting the
need to more fully consider the strategic intent and implementation of the VP. A definition would be: “a
strategic tool facilitating communication of an organization's ability to share resources and offer a superior value
package to targeted customers”.
The article addresses these calls and re-assesses the VP in the context of both strategy and implementation, by
providing a new conceptual framework.
VP origins: The value delivery system and value proposition framework: The focus of the VP depicts the business
from the customer's perspective, rather than as a series of internally-oriented functions, and consists of three
steps: (1) choose the value, (2) provide the value, and (3) communicate the value. Choosing the VP involves
assessing customer needs and determining how well an organization can satisfy those needs with clearly
differentiated benefits, relative to price, when compared with competitors. Providing the VP is concerned with
developing a product that creates clear and superior value.
Later VP stages focused more on: providing it means the customer accepts the proposition, buys the product,
and has resulting experiences; communicating means that customers have an understanding and appreciation of
experiences before, during, and after the purchase of the product.
VP evolution: A review of frameworks for VP development
1. Consultant VP frameworks: Consulting firms, large and small, offer approaches and frameworks to clients
that include VP development, but only a small number publish their approaches externally.
a. Value proposition builder: consists of six stages: (1) identify target customer segments, (2) define
customers' value in terms of benefits minus costs, (3) formulate the offer, (4) determine how the
offer provides benefits and prioritising these benefits, (5) consider competitive offerings, and (6)
provide support by way of substantiated credibility of the offering.
b. Value proposition canvas: The VP canvas seeks to achieve alignment in collaboration across the
organization in delivering value to customers. It consists of two main elements: a customer profile
and a value map. The customer profile shows, for a particular customer segment, the ‘gains’—the
nature of the jobs that customers are seeking to get done and the outcomes and benefits that
customers want to achieve—as well as the ‘pains’—obstacles and bad outcomes that relate to
customer goals. The value map focuses on the development of all the product and service features
that the VP is built around, together with a description of ‘gain creators’ (i.e., how identified
products and services create customer gains) and ‘pain creators’ (i.e., how these products and
services ease customer pains).
c. Value proposition platform: offers a sales-oriented structure for VP development. This framework
involves the development of a specification of key segments, targets in terms of key customer
decision-makers, and identification of business issues important to these decisionmakers. The
resulting VP comprises three parts: (1) a statement of the customer's objectives, (2) a concise offer
that specifically addresses the customer's objective, and (3) a statement of key differentiators,
compared to competitive offerings.
2. Academic VP frameworks: Overall, scholarly work focuses on specific aspects, rather than undertaking more
comprehensive assessments of issues related to both strategy and implementation.
a. Core benefits proposition: This framework involves developing a statement identifying the benefits
the product provides and the “fulfilment of the product promises by physical features”. This form of
proposition is especially concerned with new product design, a process that includes design,
evaluation, refinement, and fulfilment of the proposition. This form of proposition has its main
emphasis on functional features of a product.
b. Value dimensions VP framework: Evaluation of the VP's competitiveness is based on the
appropriateness of the firm's resources and competencies for delivering the VP based on clearly
differentiated benefits, amplified by an experiential focus
c. Value maps as a means of indentifying VPs: emphasize price relative to product performance. They
propose the concept of a value frontier showing the relative price/benefit trade-offs of competitors
within a particular industry sector. The authors suggest different strategies for extending or shifting
the value frontier as well as considering strategies for differentiation of VPs.
d. B2B VP framework: They conclude that resonating focus is the superior approach to crafting a VP.
Further, they argue that the building blocks of a successful VP include a comparison to the next best
competitive alternative of points of parity, points of difference, and points of contention. This
approach to VPs is the most complete with respect to B2B markets as it also places emphasis on
substantiating the VP through value quantification, value documentation, and value verification.
e. VP strategy framework: , they identify two important groups of antecedents: firm-based resources
(leadership support, extent of VP formalisation, and product knowledge) and market-based
resources (market knowledge, innovation, customer relationships, and brand reputation), which
then have a dual effect on the enterprise and its customers.
3. VP frameworks: The need for an integrative approach
Our review of the consultant and academic VP frameworks confirms a wide variety of approaches to VP
design and development. From this review, we identify ten key elements of significant importance to VP
strategy and VP implementation. As shown in Table 1, the elements relating to VP strategy include:
integration with the firm's business model, clearly differentiated value benefits based on different forms of
value, emphasis on price relative to competition, experiential focus, and emphasis on value-in-use rather
than value-in-exchange. The elements of VP implementation address: adoption of an integrated design
approach, value communication (externally to the customer and internally within the firm), value
quantification, value documentation, and value verification
Toward a comprehensive framework of VP development: The strategy context
Whilst the frameworks outlined above consider many important aspects, most provide limited consideration
of the processes that underlie VPs, which can guide managers in VP development in B2B markets. In Fig. 2,
we present a conceptual framework for VP development that addresses this gap. It comprises four parts: (1)
the business model and firm value co-creation, (2) the core value dimensions and customer value cocreation, (3) a process of co-creative VP development, including reciprocal learning, and (4) an interface with
other actors within the firm's ecosystem.
In this section we focus on the strategy context of VP development. In the section that follows, we consider
VP implementation through an examination of the VP development process shown in Fig. 2
This framework represents a departure from extant approaches to developing VPs in three key aspects.
First, it provides more detailed recognition of key strategic factors relating to the firm's business model
including strategic choices, the value creating system, the value network in which the firm exists, and the
potential for value capture. Second, it recognises the nature of co-creative practices, some of which occur in
the firm sphere, some in the customer's own, and some in a joint sphere (Grönroos & Voima, 2013). Third, it
acknowledges that VP implementation requires an integrated approach involving five interactive phases.
Specifically, in our framework, the focus shifts from internally-driven processes for developing the VP to an
interactive sequence of value design and assessment, quantification, communication, documentation, and
verification.
1. Firm value creation: Business model and value co-creation
how a firm addresses the value offered to customers and captures economic profits (Day, 2011).
Chesbrough (2010) identifies key components of a business model: competitive strategy, VP articulation,
market segments, value chain structure and requisite assets, cost structure and profit potential (i.e.,
value capture), and the value network. We identify four business model elements: strategic choices
(competitive strategy, value chain structure, value focus, and customer segment emphasis), value
creating system (cf., Day, 2006) (resources, capabilities, processes), value capture (revenue model and
cost model), and value network (strategically important actor relationships). These business model
elements collectively form the strategic basis from which target customer segments are identified and
the value requirements of the segments are identified.
2. Customer value creation: Core value dimensions and value co-creation
Value creation is a dynamic process that is experienced pre-exchange (during the process of searching,
evaluating, anticipating and deciding), during exchange (including the process of interacting), postexchange (involving “use value”), and, potentially, during disposal. There are four ‘core customer value
dimensions’ shown in: functional value, economic value, emotional value, and social value.
3. Interface with other actors
Important to recognize the impact of how these actors may interface with other relevant actors.
4. Value proposition implementation
It consists of five phases: (1) value design and assessment, (2) value quantification, (3) value
communication, (4) value documentation, and (5), value verification and VP review. In turn, the value
verification phase feeds back into the value (re)design and assessment phase.
VP co-creation is supported by critical encounters and learning activities. Within each phase, different
forms of encounter can occur, resulting in firm learning and customer learning. There are three forms of
encounters facilitating co-creation: communication encounters, usage encounters and service
encounters, which may be emotion-supporting, cognition-supporting, or action-supporting.
Learning is based on the application of knowledge. Both product knowledge and market knowledge
represent firm-based and market-based resources that are important antecedents of the VP Learning
includes three specific capabilities: capabilities that provide deep market insights and warn of market
changes and opportunities, experimentation capabilities that offer continuous learning, and
relationship-building capabilities that provide network learning opportunities. Management of these
encounters and learning activities are central to the implementation stage of VP development.
Toward a comprehensive framework of VP development: The implementation context
It provides a more detailed explanation of the five implementation phases. The five phases form a holistic
framework that illustrates how VPs are developed and shaped through design, interaction, learning, evaluation,
feedback, and renewal. The VP framework emphasizes a shift from static offerings to dynamic, reciprocal, and
co-created VPs resulting in enhanced value-in-use. Payne et al. (2017) discuss the benefits of adopting a valuein-use perspective including an illustrative case example of a B2B firm making the transition toward a more
effective value-in-use position.
Article 4.2: Johnson, M.W., C.M. Christensen and H. Kagermann (2008). Reinventing your business model.
Harvard Business Review, 86(12), 50-59.
Introduction: Executives believe business model innovation will become even more important for success than
product or service innovation. However, why is it so difficult to pull off the new growth that business model
innovation can bring? Our research suggests two problems. The first is lack of definition: Very little formal study
has been done into the dynamics and processes of business model development. Second, few companies
understand their existing business model well enough, so they don’t know when they can leverage their core
business and when success requires a new business model.
Our road map for a successful innovation model:
1. Realize that success starts by not thinking about business models at all. It starts with thinking anout the
opportunity to satisfy a real customer who needs a job done
2. Construct a blueprint laying out how your company will fulfil that need at a profit.
3. Compare that model to your existing model to see how much you’d have to change it to capture the
opportunity. Then you will see if you can use the existing model or need to separate out a new unit to
execute a new model.
Business Model: A definition: It consists of four key elements that together create and deliver value:
1. Customer Value proposition (CVP): Identifying a way to help customers get an important job (problem) done.
Opportunities for creating a CVP are at their most potent when alternative products have not been designed
with the real job in mind and you can design an offering that gets that job done perfectly
2. Profit formula: It is a blueprint that defines how the company creates value for itself while providing value to the
customer, It consists of the following:
a. Revenue Model: price x volume
b. Cost structure: direct and indirect costs
c. Margin model: given the expected volume and cost structure, the contribution needed from each
transaction to achieve desired profits
d. Resource velocity: How fast we need to turn over inventory, fixed assets and other assets to support our
expected volume and achieve our anticipated profits
3. Key resources: The assets required to deliver the value proposition to the targeted customer. The focus is on the
key elements that create value for the customer and the company, and the way those elements interact
4. Key processes: Operational and managerial processes that allow companies to deliver value in a way they can
successfully repeat and increase in scale (i.e training, manufacturing, budgeting etc)
The customer value proposition and the profit formula define value for the customer and the company. Key resources
and key process describe how that value will be delivered to both the customer and the company. All these parts are
interdependent.
How great model are built
1. Creating a customer value proposition: The most important attribute of CVP is its precision: how perfectly it nails
the customer job to be done. This is often the most difficult to achieve because companies neglect to focus on
one job. One way to generate precise customer value proposition is to think about the four most common
barriers keeping people from getting particular jobs done: insufficient wealth, access, skill or time
2. Designing a profit formula:
3. Identifying key resources and processes: Often it’s not the individual resources and processes that make the
difference but their relationship to one another. Companies will almost need to integrate their key resources
and processes in a unique way to get a job done perfectly. When they do, they almost always create enduring
competitive advantage
What a new business model is needed: Established companies should not undertake business-model innovation lightly.
They can often create new products that disrupt competitors without fundamentally changing their own business
model. So the question is WHEN it is needed? When significant changes are needed to all four elements of your existing
model. Five strategic circumstances that often require business model change:
1. The opportunity to address through disruptive innovation the needs of large groups of potential customers who
are shout out of a market entirely because existing solutions are too expensive or complicated for them
2. The opportunity to capitalize on a brand-new technology by wrapping a new business model around it or the
opportunity to leverage a tested technology by bringing it to a whole new market
3. The opportunity to bring a job-to-be-done focus where one does not yet exist. That’s common in industries
where companies focus on products or customer segments, which leads them to refine existing products more
and more. A jobs focus allows companies to redefine industry profitability.
4. The need to fend off low-end disrupters
5. The need to respond to a shifting basis of competition because inevitably what defines an acceptable solution in
a market will change over time, leading core market segments to commoditize
Article 4.3: Weinstein, A. T. (2023). Customer obsession; The springboard for a value creation strategy. Journal
of Business Strategy. (This article has not been published yet; you can download it by going to the Journal
website, where you can find it in the list of EarlyCite articles: https://www-emerald-com.proxyub.rug.nl/insight/publication/issn/0275- 6668#earlycite).
Week 5: Collaboration in innovation
Article 5.1: Faems, D., B. van Looy and K. Debackere (2005). Interorganizational collaboration and innovation:
Toward a portfolio approach. Journal of Product Innovation Management, 22(3): 238-250.
Abstract: This article examines whether evidence can be found for the idea that interorganizational
collaboration supports the effectiveness of innovation strategies. Tobit analyses reveal a positive relationship
between interorganizational collaboration and innovative performance. At the same time, the impact on
innovative performance differs depending on the nature of the partner(s) involved. These findings strongly
suggest the relevance of adopting a portfolio approach to interorganizational collaboration within the context of
innovation strategies.
Introduction: Organizing for Innovation: Innovation, and more particularly technological innovation, has long
been acknowledged as one of the critical driving forces in enhancing social welfare; likewise, innovation is seen
as crucial for the long-term survival and growth of the firm. However, managing innovation is not a
straightforward exercise. The complexities that arise when designing and implementing an innovation strategy
are directly related to the multitude of objectives such a strategy implies. Broadly speaking, innovation
strategies not only address the improvement and further development of existing technologies and products but
also the development of new technologies and competencies. Firms need to engage in both exploitation and
exploration. Whereas exploitation refers to activities such as improvement, refinement, efficiency, selection,
and implementation, exploration is best captured by notions like search, variation, experimentation, and
discovery.
In order to meet the multiple requirements that innovation strategies entail, firms tend to adopt a portfolio
approach toward organizing their new product development (NPD) activities. At the same time, it is noticeable
that firms trying to achieve this broad spectrum of innovation activities are faced with multiple, often opposing,
demands that confront them with the challenge of reconciling conflicting requirements .
There are configurations within which conflicting ingredients can coexist by adopting organizational designs that
allow for differentiating explorative activities from their mainstream exploitation-oriented counterparts.
This article examines whether interorganizational collaboration relates to the effectiveness of innovation
strategies. In other words, are firms that engage in interorganizational collaborations within the framework of
their innovation strategy performing better in terms of innovative performance? In addition, this study explores
whether this relationship—if observed—differs according to the nature of the innovation outcomes: is
interorganizational collaboration as relevant for improving existing competencies and products as for creating
new ones? In this respect, it is feasible to examine whether the notion of portfolio (i.e., pursuing a multitude of
different projects simultaneously) bears relevancy to interorganizational collaboration as well.
The role of interorganizational collaboration when Innovating: toward specific propositions:
From the present literature, it is clear that organizations can improve their innovative capabilities by developing
interorganizational collaborations with a variety of partners. The reasons why interorganizational collaboration
can contribute to the effectiveness and efficiency of an innovation strategy are numerous.
1. First, interorganizational collaboration might imply access to complementary assets needed to turn
innovation projects into a commercial success
2. Second, working together with other organizations might encourage the transfer of codified and tacit
knowledge. This might result in the creation and development of resources that would otherwise be difficult
to mobilize and to develop
3. Finally, interorganizational collaboration might help to spread the costs of research and development (R&D)
among different parties, resulting, at the same time, in a considerable reduction of the risks associated with
R&D-intensive innovation projects.
The observation that interorganizational collaboration has considerable potential to contribute to the
innovation strategies of organizations does not mean that all collaborations are successful though. Unintended
knowledge spillovers, learning races between the partners, diverging opinions on intended benefits, and lack of
flexibility and adaptability are frequently cited reasons for alliance failure. Deeds and Hill (1996) also illustrated
that the relationship between the number of collaborative agreements and innovative performance is
characterized by diminishing marginal returns. After all, the larger the number of a firm’s collaborative
agreements, the higher the risk of redundancy [i.e., the risk that different partners provide access to the same
information or complementary knowledge. Similar results were found by Baum et al. (2000), arguing that it is
not the number of collaborative agreements per se but rather the diversity of the firm’s alliance network1 that
influences the innovative performance of the firm. These findings suggest that organizations that possess a
diverse network of interorganizational collaboration are better equipped to create and to commercialize new or
improved products.
We have distinguished between explorative and exploitative collaborations. While the intent behind entering an
exploration alliance involves a desire to discover new opportunities, an exploitation alliance involves the joint
maximization of complementary assets. Explorative and exploitative collaborations have different effects on a
firm’s innovation strategies.
1. In exploitative collaborations, the main purpose relates to the enhancement of existing organizational
competencies. More specifically, exploitative collaboration centers on leveraging existing skills. Exploitationoriented collaboration processes benefit from clear performance objectives that are translated into
measurable output controls and are monitored by formalized coordinating and control mechanisms
H2: The more a firm engages in exploitative interorganizational collaborations, the more effective it will be in
terms of improving and further developing existing technologies and their implied products.
2. Explorative collaboration, on the other hand, is seen as instrumental in creating new competencies; learning
processes and joint experimentation figure prominently in this type of collaboration. Hence, a differential
emphasis in the direction of intangible or tacit knowledge exchange can be observed. To achieve such
learning objectives, alliance partners rely more on personal and informal modes of coordination and control
H3: The more a firm engages in explorative interorganizational collaborations, the more effective it will be in
terms of developing new technologies and/or products.
Discussion: Firms that possess a heterogeneous network of collaborative partners within the framework of their
innovation strategies perform better in terms of the proportion of turnover realized by means of new or improved
products. In addition, the difference between exploitative and explorative collaborations has been introduced to
examine whether different kinds of collaboration relate to different types of innovation outcomes. This study
hypothesized that exploitative-oriented collaborations could support the improvement and further development of
existing technologies and products, while explorativeoriented collaborations would be beneficial for innovation
objectives aimed at creating new technologies and products. These hypotheses have, to a large extent, been confirmed.
Collaborations with customers and suppliers—labeled as ‘‘exploitative’’—are associated positively with higher levels of
turnover stemming from improved products, while collaborations with universities and research organizations—labeled
as ‘‘explorative’’—are associated in similar fashion with turnover levels related to new products.
Relevance for practitioners: This study’s findings suggest that companies should consider the idea of a portfolio of
interorganizational arrangements when implementing their innovation strategies in order to be effective in developing
improved and new technologies and products. It was observed during this study that interorganizational collaboration
with different partners (customers and suppliers versus universities and research centers) contributes to the innovative
performance of firms, while, at the same time, the observed relationships differ depending on whether one looks at
performance stemming from improved or new development efforts. Since the effects of collaborating with different
partners are, at the same time, significant and of a different nature, the relevancy of extending the idea of adopting a
portfolio approach to interorganizational collaboration comes to the forefront. This study’s findings suggest a supportive
role for a portfolio of different, though complementary, interorganizational arrangements for achieving innovation
outcomes. To the extent that firms strive for multiple innovation outcomes, their innovation strategy might entail an
appropriately balanced set of interorganizational collaborative arrangements.
Conclusion: The purpose of this study was to assess whether the collaborative behavior of organizations relates to the
innovative output of these organizations. Based on these results, it can be concluded that the more firms engage in a
variety of different interorganizational collaborations, the more likely they are to create new or improved products that
are commercially successful. Moreover, this study showed that collaboration with different types of partners coincides
with different types of innovation outcomes. These results highlight the relevance for senior management of adopting a
portfolio approach to interorganizational collaborations in order to achieve results both in terms of developing existing
technologies and creating new ones.
Article 5.2: Brandenburger, A. and B. Nalebuff (2021). The rules of co-opetition. Harvard Business Review, 99(1): 48-57.
Idea in brief:
1. The context: The idea that competitors should sometimes cooperate with one another has continued to gain
traction since it was initially explored in the 1990s.
2. The issue: Even so, executives who aren’t comfortable with “co-opetition” bypass promising opportunities.
3. A framework for action: Start by analyzing what each party will do if it doesn’t cooperate and how that decision
will affect industry dynamics. Sometimes cooperation is a clear win. Even if it isn’t, it may still be preferable to
not cooperating. But it’s critical to try to figure out how to cooperate without losing your current advantages.
Introduction: There is a name for the mix of competition and cooperation: co-opetition. There are many reasons for
competitors to cooperate. At the simplest level, it can be a way to save costs and avoid duplication of effort. If a project
is too big or too risky for one company to manage, collaboration may be the only option. In other cases one party is
better at doing A while the other is better at B, and they can trade skills. And even if one party is better at A and the
other has no better B to offer, it may still make sense to share A at the right price.
Co-opetition raises strategic questions, however. How will the competitive dynamics in your industry change if you
cooperate—or if you don’t? Will you be able to safeguard your most valuable assets? Careful analysis is required. In this
article we’ll provide a practical framework for thinking through the decision to cooperate with rivals.
What is likely to happen if you don’t cooperate?
If a cooperative opportunity is on the table, start by imagining what each party will do if it’s not taken. What alternative
agreements might the other side make, and what alternatives might you pursue? If you don’t agree to the deal, will
someone else take your place in it? In particular, will the status quo still be an option?
Will cooperation give away your competitive advantage?
Suppose you’ve analyzed the alternatives to cooperation and tentatively decided to move ahead. Doing so may mean
sharing your special sauce. Then it might not be so special, and that could be a real problem. To get a read on the
potential risk, figure out which of these four categories the deal falls into:
1. Neither party has a special sauce at risk, but the parties’ combined ingredients create value. In this scenario
neither side is giving anything away. It’s not unusual for rivals to team up to set standards and create
interoperability protocols and thereby create a bigger pie they can later fight over.
2. Both parties have a special sauce, and sharing puts them both ahead of their common rivals.
3. One party has a strong competitive advantage, and sharing only heightens it; even so, less-powerful parties
are willing to cooperate.
4. One party shares its secret sauce to reach another’s customer base, even though doing so carries risks for
both parties. It isn’t always possible to rent the sauce without giving away the recipe, however. Could the
United States and China, for instance, cooperate on a mission to Mars? A seemingly insurmountable challenge is
that it would involve sharing intellectual property that can’t be recaptured. This is a particularly sensitive issue
since space technology spills over to military applications.
How to structure an agreement: Two issues are particularly challenging when a prospective partner is also a competitor:
the scope of the deal and how the costs and benefits will be divided. (There may also be antitrust concerns;
1. Establishing scope and control. First the parties have to figure out how far to extend their cooperation, who is in
charge, and how they might unwind their arrangement should it no longer make sense. The simplest types of
cooperation are limited and don’t raise control issues. In some cases one party becomes a nonessential supplier
to the other. In other cases the parties share costs but not proprietary knowledge. Generally these
arrangements are easy to negotiate and can be unwound easily.
Agreements become challenging when one party has to cede control, however. In other circumstances one
party is in charge and the other party is protected by a contingent contract with performance guarantees and
penalties for not hitting specific targets. This works well in situations where there are established performance
benchmarks. The party in charge, the one providing the guarantees, doesn’t have to be told what to prioritize;
instead the right-sized penalties allow it to internalize decisions and make calls that optimize the combined
outcome. It’s important to structure any agreement in such a way that one side doesn’t become dependent on
the other. Otherwise, the dependent party may be backed into a corner when it comes time to renegotiate the
deal—or distressed when the deal ends
2. Dividing the pie. Cooperation is an overall win-win, but splitting the gains is a zero-sum game. The solution is
relatively straightforward when there’s an even trade. It’s harder if cooperation involves an uneven trade and
payments are required.
Changing minds: Cooperation with rivals also has an important emotional aspect. Some people are comfortable with the
idea that there can be multiple winners, and some are not. As a result, co-opetition may end up being a strategy of last
resort even in cases where it should be a first resort. Obvious opportunities for cooperation fall by the wayside when
businesspeople don’t focus on ensuring that all parties come out ahead.
ULTIMATELY, GET TING THE right mindset requires choosing the right people. The executives we interviewed
emphasized the need to staff the cooperating teams with people who are open to the dual mindset of co-opetition. That
isn’t always easy, because people tend to think in either/or terms, as in either compete or cooperate, rather than
compete and cooperate. Doing both at once requires mental flexibility; it doesn’t come naturally. But if you develop that
flexibility and give the risks and rewards careful consideration, you may well gain an edge over those stuck thinking only
about competition.
Article 5.3: Chaudhary, S., P. Kaur, S. Talwar, N. Islam and A. Dhir (2022). Way off the mark? Open innovation failures:
Decoding what really matters to chart the future course of action. Journal of Business Research, 142, 1010-1025.
(not my best work, ngl)
Abstract: With the increasing need for firms to implement innovation in their pursuit of competitive advantage, open
innovation has attracted the growing attention of academics and practitioners. We argue that eulogising only the
positive aspects of open innovation is insufficient to help firms and motivate future research. Therefore, we recommend
increased attention to the dark side of open innovation, which includes failures that can occur at various stages of the
open innovation process. The contributions of this SLR (systematic literature review) include (a) development of a
research profile of the relevant literature, (b) identification of five thematic areas, (c) elucidation of research gaps and
suggestion of potential research questions as an agenda for future research on failures in open innovation, (d)
formulation of a conceptual framework comprising the antecedents and outcomes of open innovation failure and (e)
presentation of the various theoretical and managerial implications for scholars and practitioners
Introduction: Over the past three decades, the concept of open innovation has gained tremendous popularity among
academics and practitioners. Traditionally, firms invested in developing technologies internally and later commercialised
them by offering new products and services. Lately, however, the increasing mobility of knowledge workers, the
complexity of the environment, the emergence of venture capitalists and accelerators and globalisation have
undermined the efficacy of traditional innovation and highlighted the crucial need for the input of external knowledge.
Open innovation—defined as purposive knowledge inflow and outflow using monetary and non-monetary
mechanisms—is now theorised to be the key driver of competitive advantage. This is because investment in open
innovation allows the acquisition of external knowledge and technologies to complement the internal development of
technologies ); open innovation, moreover, enables the deployment of internal and external sources of ideas to sustain
and commercialise innovation. In sum, the idea of open innovation is aligned with the long-standing notion that no
organisation can innovate in isolation; instead, every organisation must engage with the external environment to
capitalise on the input of new ideas
A review of the literature reveals that the concept of open innovation has gained traction due to the various inherent
benefits it brings. These benefits include
(a) addressing the problems related to the growing complexity of the external environment, technological
advancements, shorter product life cycles and the erosion of boundaries between firms and their environment
(b) facilitating faster market response and increased market access
(c) helping organisations resolve their innovation-related issues, which ultimately results in value creation and
(d) supporting firms as they transcend their boundaries while creating and commercialising innovations by capturing
generated value
In brief, open innovation exemplifies the enrichment of knowledge (Dodgson, Gann, & Salter, 2006) and drives
competitive advantage in highly uncertain environments
Some challenges concerning open innovation: challenges based upon different types of open innovation, such as
inbound open innovation and outbound open innovation
1. First, organisations may face barriers while recognising and integrating external information
2. Second, integrating the diverse external information gathered from varied sources within an organisational
context is costly because firms have yet to enhance their knowledge assimilation ability
3. Third, organisations may face intellectual property issues concerning innovations developed with external
collaborators
4. Fourth, potential appropriation issues act as barriers to leveraging the benefits of outbound innovation
5. Finally, knowledge spillovers are regarded as inherently and unmanageable
To our knowledge, the current study is the first to review the literature around failures in open innovation and
contributes to the area by providing a holistic picture of the risks and costs associated with open innovation failure.
Open innovation: Benefits and failure
Open innovation, which entails managing knowledge flows across the organisational boundary, describes the
phenomenon by which an organisation uses external ideas and technologies and allows unused technologies to be
exploited by others. The success of open innovation depends upon the firm’s ability to create and capture value using
pecuniary and non-pecuniary mechanisms. To explain further, value creation implies an organisation’s attempt to
generate new, valuable resources and achieve desired goals through the open innovation. In comparison, value capture
implies securing the value created during the process of open innovation. In sum, the notion of open innovation is based
on the creation and utilisation of widely distributed knowledge.
Open innovation failure represents the downsides of openness, such as appropriation challenges, transformation of
knowledge, and lack of stakeholder commitment, which together comprise the high cost of open innovation. Other
reasons for open innovation failure discussed by prior studies include risk aversion, lack of trust, resistance to change
and rigid organisational cultures. In light of these challenges, firms must apply both formal processes (such as
intellectual property rights and patents) and informal processes (such as trust and relational capabilities) to manage
knowledge flows. Going beyond the general discussion of open innovation failure, some studies have discussed failures
related to specific types of innovation, i.e. inbound, outbound and coupled innovation
Types of innovation: Inbound, outbound, and coupled:
1. Inbound Innovation
Inbound innovation enriches the organisation’s existing knowledge base through partnerships with suppliers,
customers, consulting companies, competition and other external knowledge sources. The benefits of inbound
innovation include the ability of firms to recognise and access external knowledge, which allows them to
reconfigure existing internal knowledge. Moreover, access to external knowledge reduces the time required for
product development, thereby enabling firms to swiftly achieve product development goals and improve access
to existing and new markets
2. Outbound innovation
Outbound innovation means leveraging technologies by allowing internally generated ideas to flow outward,
selling intellectual property rights and transferring technologies to external organisations. Organisations
investing in outbound innovation focus on externalising their innovations and bringing internal ideas to the
market more quickly. In sum, outbound open innovation represents the outflow of a firm’s knowledge to
external subjects
3. Coupled innovation
It describes bi-directional knowledge exchanges. It also implies the combined employment of purposeful inflows
and outflows to and from an organisation with a view to commercialising an innovation. Specifically, it entails
innovation through a set of inter-firm relationships, such as alliances and joint ventures, which allow access to
complementary knowledge
Thematic areas:
1. Cost of openness:
The premise of openness encompasses the voluntary and non-voluntary disclosure of information to
outsiders. We find an agreement in the literature that openness increases the alertness of firms to new
market opportunities and provides access to external knowledge. On the flip side, however, openness also
results in the generation of excessive amounts of data. Thus, firms face a constant dilemma: while openness
increases alertness and access to new knowledge, this broad access to external knowledge produces a large
volume of data that leads to high integration costs. In sum, the cost of openness entails the over-search of
external knowledge and the high integration cost of the data thus generated
2. Firm-level challenges:
organisations must invest in R&D capabilities to effectively grasp external knowledge. In this regard, prior
literature has discussed knowledge management challenges in open inbound innovation related to costs
associated with the acquisition, assimilation and integration of external knowledge. Apart from the
knowledge management challenges, a comprehensive review of the literature reveals numerous intra-firm
and inter-firm mechanisms that can impede the success of open innovation. The success or failure of open
innovation depends upon the ways in which resources are developed and utilised during knowledge sharing
The lack of fit between external technology and a firm’s business model has been identified as among the
reasons for open innovation failure.
Similarly, past studies have considered several inter-firm factors as potential barriers. For instance, Greco et
al. (2019) noted that open innovation depends upon the nature of the relationship between partner firms,
which can create potential barriers and lead to the failure of open innovation. In particular, external
partners must be convinced to share relevant external knowledge (Salge et al., 2013). This indicates that a
lack of trust represents a potential barrier to inter-firm cooperation
3. Individual-level challenges
another stream of research emphasises the need to understand the role of individuals, such as employees,
customers and users. As gatekeepers in value creation opportunities, individual employees are exposed to
numerous challenges because they must continuously interact with the external environment. The potential
loss of value due to employees’ misappropriation of knowledge can act as a barrier to the success of open
innovation. In addition, customers’ perceptions of resource misutilisation are a crucial driver of co-creation
or co-destruction. Specifically, customers are likely to participate in codestruction when they perceive an
organisation misusing resources during the open innovation process (Hsu et al., 2021). In brief, the
perceived unfairness of open innovation outcomes may result in unrest and negative word of mouth,
adversely influencing open innovation outcomes
In sum, past studies have shown that because open innovation is a multi-level phenomenon, its success
depends upon micro-level factors. Expounding upon this thought, the literature has highlighted the role of
an individual’s prior experience and knowledge, emotions, and perceptions in impacting open innovation
outcomes.
4. Types of open innovation and failure (inbound, outbound, coupled open innovation)
a. In the case of inbound open innovation, the associated costs are a grave concern because this type of
innovation requires firms to invest in implementing a market intelligence system, which results in high
search costs. In addition, geographical and cultural distance as potential barriers to the source of
external knowledge can also be quite high
b. A review of the literature reveals different obstacles that often prevent firms from leveraging the
benefits of outbound innovation. These obstacles exist due to firms’ disinclination to commercialise
technologies for the following reasons. First, knowledge hoarding within organisations may happen
because of the over-evaluation of internally generated knowledge and the perceived risk of sharing
potential ideas with the outside world. Second, the overcommitment of firms to commercialise the
benefits of open innovation in-house as well as potential intellectual property rights issues may prevent
firms from leveraging the benefits of outbound innovation. Third, firms may lack a strategy for
commercialising the benefits of outbound innovation
c. Finally, we enumerate challenges related to coupled innovation, which encompasses both inbound and
outbound innovation. First, organisations may face challenges while pursuing coupled open innovation
due to possible concerns related to intellectual property infringement and costs related to identifying
appropriate partners for technology collaborations. Second, organisations may face tension between
knowledge protection and knowledge sharing due to the diversity of partners, and this tension may
result in knowledge management challenges
5. Contingent/moderation mechanisms
A review of the relevant literature further reveals that variance in the open innovation performance
relationship is due to various contingent/ moderation mechanisms. Accordingly, the extant research has
theorised the crucial role of contingent/moderation mechanisms, including internal and external factors.
a) Internal factors include knowledge-related mechanisms, such as in-house R&D capabilities etc. These
internal factors the strengthen open innovation performance.
Conceptual framework:
Content analysis of selected studies in our SLR helped us identify the dominant themes and research gaps that
call for further research. Accordingly, building upon our insights obtained from the thematic analysis, we
propose a framework comprising the antecedents, moderators, and outcomes of open innovation.
Our framework presents two broad antecedents of open innovation failure: firm- and individual-level factors.
The former is captured through inter-firm and intra-firm factors. These factors are identified on the basis of their
ability to influence open innovation outcomes.
1. The inter-firm factors include cognitive and cultural challenges, trust issues, goal complementarity and
appropriation while the intra-firm factors include the level of openness, knowledge management processes,
governance, leadership, lack of resources and capabilities and business model fit. Regarding the inter-firm
factors, we recommend a deeper investigation of the ways in which competitive relationships can impinge
upon the success/failure of the open innovation process.
2. In the case of intra-firm factors, we posit that it is critical to understand how firms leverage individual
knowledge by examining the ways in which organisational strategies shape individual-level openness and
the potential pitfalls of data breaches and privacy issues
Similarly, past studies have established that the success or failure of open innovation depends upon individual-level
factors. , we argue that the inclusion of individual-level factors, theorised in our conceptual framework to include
emotions, motivations, competencies and prior experience, can serve to better illuminate open innovation failure.
Succinctly, we reinforce the fact that open innovation success or failure depends upon individual-level factors and
factors internal and external to the firm, and we call for a deeper investigation of each.
The thematic analysis reported in the preceding parts suggests the importance of utilising individual and demographic
variables, such as individual age, gender and education; firm age, size, industry and level of technology applied; and
other moderating variables in future studies to better explain the hypothesised associations.
Week 6: Multinational teams
Article 6.1: Tenzer, H., M. Pudelko and M. Zellmer-Bruhn (2021). The impact of language barriers on knowledge
processing in multinational teams. Journal of World Business, 56(2): 101184.
Abstract: This qualitative study investigates how language diversity in multinational teams affects
communication, which, in turn, influences knowledge processing. We show that evident language barriers (lack
of lexical and syntactical proficiency) reduce participation in team communication, which impedes both basic
and sophisticated knowledge processing activities. We also demonstrate that hidden language barriers
(pragmatic and prosodic transfer between mother tongues and working language) impair sensemaking in the
team, which disrupts sophisticated knowledge processing activities. By highlighting the relevance of hidden
barriers, our study encourages a more comprehensive conceptualization of language barriers and uncovers the
micro-foundations of knowledge processing in multilingual teams. Contrasting evident and hidden barriers, our
study juxtaposes the instrumental and the cultural perspective on language. By distinguishing basic and
sophisticated knowledge processing activities, we weigh the information processing against the socio-cognitive
perspective on knowledge. We integrate these divergent perspectives on language and knowledge processing
both within and across the respective research fields.
Introduction: Multinational teams (MNTs) are paramount for global collaboration, particularly for knowledge
processing within MNC units. As teams are defined by the interdependency between their members, they rely
on intense communication to align their members’ contributions. This communication is highly vulnerable to
language barriers, since MNTs not only include members of different national and cultural backgrounds but
typically also unite speakers of different mother tongues.
To date, IB language research has mostly been concerned with language proficiency problems, assuming that
barriers can be removed by increasing MNT members’ fluency in their team’s working language (Peltokorpi &
Vaara, 2014). Countering this general position, some IB studies assert that communication is bound by the sociocognitive contexts of conversation partners (Konig, ¨ Fehn, Puck, & Graf-Vlachy, 2017) and that culture
influences how language is used (Chen, Geluykens, & Choi, 2006; Kassis Henderson, 2005; Wang et al., 2018),
suggesting that the influence of language on MNT knowledge processing may be more complex.
RQ 1: How do language barriers affect communication in MNTs?
RQ 2: How do language-induced communication impediments affect MNT knowledge processing?
Regarding RQ 1, our qualitative research highlights the relevance of two kinds of language barriers MNT
members are facing, namely evident and hidden barriers, and their adverse impact on participation and sense
making in MNT communication
Discussion: In response to RQ 1, we established that evident language barriers lead to reduced participation in
team communication and hidden language barriers to impaired sensemaking. In addressing RQ 2, we uncovered
how those language-induced communication impediments obstruct simple and sophisticated knowledge process
activities of MNTs.
In the following, we explain how our discovery of two kinds of language barriers reveals fundamentally different
language effects in MNTs; we show how the instrumental and cultural perspectives on language complement
each other; and we connect our language-related contributions with our contributions to knowledge processing
research.
Our study shows that higher working language proficiency of MNT members does not automatically ensure
smooth knowledge processing. On this basis, our findings highlight the additional relevance of hidden language
barriers resulting from pragmatic and prosodic differences. Whereas evident language barriers lead to reduced
participation in team communication, hidden language barriers interfere with team members’ sensemaking. The
latter appear particularly disruptive because misunderstandings often go unnoticed and remain unaddressed.
When team members finally feel the consequences, they rarely recognize them as language-related and keep
persistent misapprehensions about colleagues and collaboration. These pernicious hidden barriers are very
pervasive, as even MNT members with high lexical and syntactical proficiency in the team’s working language
transfer the specific pragmatic and prosodic conventions of their native tongue to this language
(honestly this article is shitty and incredibly useless/irrelevant in my opinion...I’m stopping here.)
Article 6.2: Super, J. F. (2020). Building innovative teams: Leadership strategies across the various stages of team
development. Business Horizons, 63(4): 553-563.
Abstract: Globalization, advances in technology, and shifting consumer preferences affect almost everyone.
Because of pressures from the external environment, organizations face rapid and constant change. The nature
of work has become complicated; it is difficult for individuals to achieve much on their own. Consequently,
organizations rely heavily on expert, innovative work teams. These highly evolved teams do not develop
overnight; rather, they evolve and develop in stages, and the team’s leadership must change over time. In this
article, I present the building blocks of team innovation, outline the internal processes that lie at the core of
innovative performance, and provide critical leadership strategies for each stage of team development. I
conclude with implications for developing leaders with the capabilities to nurture and build innovative teams.
Innovation teams: Achieving excellence in a constantly changing world
The nature of work is now more complex. It has become almost impossible for an individual to complete a
complicated task alone. In response, companies have flattened organizational structures, pushed decisionmaking down to the lowest levels, and relied heavily on teams. Teamwork has become so essential that teams
have become the building blocks of organizations.
Recent research has focused on innovative teams. The needs of these teams are extremely complex (Mumford,
Robledo, & Hester, 2011). In particular, innovative teams require a supportive organizational environment,
psychological safety, diversity, communication, and continuous learning (Edmondson, 2012; Mumford et al.,
2011). However, the research on team innovation is relatively new. This article addresses that knowledge gap. I
present the building blocks of team innovation and outline the internal processes that lie at the core of
innovative performance. Then, I look at the various stages of innovative team development and provide
suggested leadership strategies for each of these stages. To conclude, I discuss implications for training team
leaders.
The building blocks of team innovation: innovative teams are involved in the creative process: generating ideas,
exploring, and experimenting. As such, innovation requires learning, and learning requires information. Teams
obtain new information via new team members. As new members join the team, they add their knowledge to
the team’s informational resources, which can enhance the innovative capacity of the team. Innovative capacity
increases when newcomers are diverse, offer unique perspectives, and feel comfortable sharing their
knowledge. The team also acquires new knowledge through individual learning.
However, acquiring information is not enough. Teams must use that information effectively in order to achieve
innovative outcomes. Four factors contribute to an innovative team climate: (1) a shared objective and vision;
(2) the safety to speak up and voice an opinion; (3) a common and shared commitment to task excellence; and
(4) organizational support for innovation
Inside team innovation: The task engagement and learning cycle:
Article 6.3: Swart, K., T. Bond-Barnard and R. Chugh (2022). Challenges and critical success factors of digital
communication, collaboration and knowledge sharing in project management virtual teams: A review.
International Journal of Information Systems and Project Management, 10(4), 84-103.
Abstract: Technological advancements, globalization, and the COVID-19 pandemic have transformed digital
communication into a central tenet of many project management virtual teams (VTs). However, successful
VTs are dependent on communication, collaboration and knowledge sharing among team members.
Through a systematic literature review, this study investigates the challenges and critical success factors
of digital communication, collaboration, and knowledge sharing in project management VTs. As a result, eight
key common themes were identified -trust, cultural diversity, collaboration tools and technology,
communication and knowledge hoarding, leadership, psychological safety, communication guidelines and
training, and resource planning. Furthermore, given the geographically dispersed nature of VTs, they face
additional challenges than teams that interact face-to-face (in-person). Therefore, mitigating the challenges
by focusing on the identified themes could lead to project success
Introduction: many organizations have adopted virtual ways of working, either through fully virtual project
teams or a hybrid-based approach. With project tasks continuously growing in complexity for geographically
dispersed and electronically dependent teams, internet-related technologies have become necessary
forproject execution and stakeholder communication.
Digital communication refers to the process of sharing information, messages and ideas with others over
a particular time and place, with the aid of digital channels and devices [10]. However, digital
communications pose several challenges that traditional face-to-face communication typically does not,
requiring teams to adapt. One such team adaption is the use of ‘swift trust’, which refers to situations
whereby members of a VT transfer trust from other familiar settings by utilizingstereotypical impressions of
each other [11]. The most prevalent challenges digital communication faces are categorized into three main
areas. The first relates to information security risks, such as data privacy, confidentiality and security
issues. The second challenge relates to the technology that inhibits efficient and effective communication.
The last relates to ineffective leadership and inadequate resource planning
Results: The onset of VTs has had a substantial impact on how teams communicate and can assist firms
in mitigating risk, minimizing operation costs, and eliminating redundancy of tasks [20]. A significant
portion of the academic literature focuses on how digital platforms influence team interaction and the
key success factors that allow VT to collaborate effectively [7, 21, 22]. Moreover, Evans [23]states that
“collaboration and knowledge sharing are fundamental aspects of problem-solving, decision making and
innovation, and are therefore vital for success” (p. 175).Chen et al. [24]focused on the development of a trust
evaluation method between team members in VTs to ensure co-workers effectively share information and
collaborate, and found that effective management, resource planning and trust facilitate maximum
collaboration. Similarly, Verburg et al. [7]identified critical success factors for project management with
similar recommendations that included clear rules for communication, management competency, and team
trust. A common theme highlighted in various academic papers was how multicultural teams alter team
dynamics and trust and that team members lack the skills to work with people of diverse cultures
Based on the systematic literature review, eight key common themes were identified. A conceptual model (see
Figure 3) was developed to visually illustrate how the eight themes related to the overarching question of digital
communication, collaboration and knowledge sharing in virtual teams. First, collaboration tools and technology
form the core foundation for VTs to operate, as, without such technology, the concept of VTs ceases to exist.
Second, in most instances, cultural diversity (indicated by the second dotted line) will be present in VTs,
specifically in dispersed settings. Cultural diversity has both a direct and indirect impact on how VTs
collaborate. Third, four pillars form the basis of effective communication, collaboration and knowledge
sharing, namely effective resource planning (where the correct individuals are selected based on the
task at hand), trust between team members, effective leadership and well-defined communication guidelines
and training. These four pillars result (arrowheadpointing down) in psychological safety that further enhances
communication and reduces knowledge hoarding within a VT context
Discussion & conclusion: This study provided an overview of the challenges and critical success factors of
digital communication, collaboration and knowledge sharing typically faced in project management virtual
teams (VT). Based on a review of VT-related literature, it is evident that additional challenges exist for
VTs compared to traditional face-to-face teams, given their often geographically dispersed nature and
heavy reliance on digital collaboration technology. However, researchers agree that virtual means of
working offer team members more flexibility regarding time andlocation of work [31, 49]. The findings of the
reviewed literature corroborate the generally held view that communication, collaboration and knowledge
sharing in VTs is more challenging than in traditional face-to-face teams; hence VTs require additional
support. The eight identified themes are summarized in Table 1. These themes are viewed as the key factors
that are significantly different from traditional face-to-face teams, requiring a more meticulous planning
approach to enable VTs to execute their defined goals successfully.
One of the principal findings from this review was the significance of trust in virtual settings and that
VT members require an additional sense of trust on a personal and process/system level [1, 28, 44]. The
literature recommended that all team members meet face-to-face/in person during the inception and
organization phases of the project lifecycle in order to establish individual trust during the early phase
of project execution, with a hybrid model being the ideal approach to maximize team collaboration and
knowledge transfer thereafter [25, 42]. In addition to individual trust, team members need to trust the
systems and technology used to communicate and collaborate [28]. Psychological safety should be embedded
by allowing team members to be open and candid, think outside the box and discuss novel ideas without fear
of retribution [32]. Leaders are seen as the shapers of a psychologically safe team culture in which they
enable VT members to feel safe to share ideas, offer constructive criticism and seek help [35].Technology was a
critical foundation for digital communication, with the recommendation of using a combination of first,
second and third-generation collaboration technology [34]. Given the media richness of third-generation
collaboration technologies, such as video conferencing tools, it is advisable to use them for large and
complex information exchanges, particularly those that involve knowledge-sharing activities. Virtual team
members should be provided with adequate training and technical support to become competent in
using the selected technology [39]. Furthermore, appropriate virtual communication guidelines that outline
how team members should interact and share should be developed and followed.
The benefits of cultural diversity must be leveraged rather than seeing it as a challenge. Cultural
diversity provides a rich diversity of perspectives, skills and knowledge that must be adequately utilized.
In order to minimize VT conflict and knowledge hoarding, teams need to develop cultural intelligence and
access cultural diversity training [26, 27]. Virtual team leaders have an essential role in their teams’
implementation, functioning and cohesiveness. They must strategically select digital communication
technologies and human resources to suit the virtual working environment. Likewise, virtual leaders need
to have skills and traits to enhance VT resilience. The study showed that the eight identified themes
contribute distinctively, but often in overlapping ways, to the challenges and critical success factors of
digital communication, collaboration and knowledge sharing in project management VTs. Furthermore,
given the recent shift by many firms to work either on a pure virtual or hybrid model, the obligation of VTs to
effectively communicate, collaborate and execute project deliverables is noteworthy. Therefore, VTs need
to be aware of the peculiarities, challenges and success factors that are integral to executing projects
virtually. Additional training may be required for teams to adjust to the new virtual working methods.
Week 7: Knowledge management and the dark side of innovation
Article 7.1: Thomke, S. and J. Manzi (2014). The discipline of business experimentation. Harvard Business
Review, 92(12): 70-79.
Abstract: big data can provide clues only about the past behavior of customers—not about how they will react
to bold changes. When it comes to innovation, then, most managers must operate in a world where they lack
sufficient data to inform their decisions. Consequently, they often rely on their experience or intuition. But ideas
that are truly innovative—that is, those that can reshape industries—typically go against the grain of executive
experience and conventional wisdom. Managers can, however, discover whether a new product or business
program will succeed by subjecting it to a rigorous test.
Why don’t more companies conduct rigorous tests of their risky overhauls and expensive proposals? Because
most organizations are reluctant to fund proper business experiments and have considerable difficulty executing
them. Although the process of experimentation seems straightforward, it is surprisingly hard in practice, owing
to myriad organizational and technical challenges.
Does the experiment have a clear purpose? Companies should conduct experiments if they are the only practical
way to answer specific questions about proposed management actions. In many situations executives need to
go beyond the direct effects of an initiative and investigate its ancillary effects.
Hava the stakeholders made a commitment to abide by the results? Before conducting any test, stakeholders
must agree how they’ll proceed once the results are in. They should promise to weigh all the findings instead of
cherry-picking data that supports a particular point of view. Perhaps most important, they must be willing to
walk away from a project if it’s not supported by the data. Of course, there might be good reasons for rolling out
an initiative even when the anticipated benefits are not supported by the data. But if the proposed initiative is a
done deal, why go through the time and expense of conducting a test?
A process should be instituted to ensure that test results aren’t ignored, even when they contradict the
assumptions or intuition of top executives. Proposals go through a filtering process in which the first step is for
finance to perform an analysis to determine if an experiment is worth conducting. For projects that make the
cut, analytics professionals develop test designs and submit them to a committee that includes the vice
president of finance. The experiments approved by the committee are then conducted and overseen by an
internal test group. Finance will approve significant expenditures only for proposed initiatives that have adhered
to this process and whose experiment results are positive.
Is the experiment doable? Experiments must have testable predictions. But the “causal density” of the business
environment—that is, the complexity of the variables and their interactions—can make it extremely difficult to
determine cause-and-effect relationships. Learning from a business experiment is not necessarily as easy as
isolating an independent variable, manipulating it, and observing changes in the dependent variable.
Environments are constantly changing, the potential causes of business outcomes are often uncertain or
unknown, and so linkages between them are frequently complex and poorly understood.
To deal with environments of high causal density, companies need to consider whether it’s feasible to use a
sample large enough to average out the effects of all variables except those being studied. Unfortunately, that
type of experiment is not always doable. The cost of a test involving an adequate sample size might be
prohibitive, or the change in operations could be too disruptive. In such instances, as we discuss later,
executives can sometimes employ sophisticated analytical techniques, some involving big data, to increase the
statistical validity of their results.
That said, it should be noted that managers often mistakenly assume that a larger sample will automatically lead
to better data. Indeed, an experiment can involve a lot of observations, but if they are highly clustered, or
correlated to one another, then the true sample size might actually be quite small. When a company uses a
distributor instead of selling directly to customers, for example, that distribution point could easily lead to
correlations among customer data. The required sample size depends in large part on the magnitude of the
expected effect. If a company expects the cause (for example, a change in store name) to have a large effect (a
substantial increase in sales), the sample can be smaller. If the expected effect is small, the sample must be
larger.
How can we endure reliable results?
1. Randomized field trials. Randomization plays an important role: It helps prevent systemic bias, introduced
consciously or unconsciously, from affecting an experiment, and it evenly spreads any remaining (and
possibly unknown) potential causes of the outcome between the test and control groups. But randomized
field tests are not without challenges. For the results to be valid, the field trials must be conducted in a
statistically rigorous fashion. Instead of identifying a population of test subjects with the same
characteristics and then randomly dividing it into two groups, managers sometimes make the mistake of
selecting a test group (say, a group of stores in a chain) and then assuming that everything else (the
remainder of the stores) should be the control group
2. Blind tests. “blind” tests, which help prevent the Hawthorne effect: the tendency of study participants to
modify their behavior, consciously or subconsciously, when they are aware that they are part of an
experiment.
3. Big data. In online and other direct-channel environments, the math required to conduct a rigorous
randomized experiment is well known. But as we discussed earlier, the vast majority of consumer
transactions occur in other channels, such as retail stores. In tests in such environments, sample sizes are
often smaller than 100, violating typical assumptions of many standard statistical methods. To minimize the
effects of this limitation, companies can utilize specialized algorithms in combination with multiple sets of
big data
For any experiment, the gold standard is repeatability; that is, others conducting the same test should obtain
similar results. Repeating an expensive test is usually impractical, but companies can verify results in other ways
Have we gotten the most value out of the experiment? Many companies go through the expense of conducting
experiments but then fail to make the most of them. To avoid that mistake, executives should take into account
a proposed initiative’s effect on various customers, markets, and segments and concentrate investments in
areas where the potential paybacks are highest. The correct question is usually not, What works? but, What
works where? Another useful tactic is “value engineering.” Most programs have some components that create
benefits in excess of costs and others that do not. The trick, then, is to implement just the components with an
attractive return on investment (ROI).
Moreover, a careful analysis of data generated by experiments can enable companies to better understand their
operations and test their assumptions of which variables cause which effects. With big data, the emphasis is on
correlation—discovering, for instance, that sales of certain products tend to coincide with sales of others. But
business experimentation can allow companies to look beyond correlation and investigate causality—
uncovering, for instance, the factors causing the increase (or decrease) of purchases. Such fundamental
knowledge of causality can be crucial. Without it, executives have only a fragmentary understanding of their
businesses, and the decisions they make can easily backfire.
What’s important here is that many companies are discovering that conducting an experiment is just the
beginning. Value comes from analyzing and then exploiting the data.
Challenging conventional wisdom: By paying attention to sample sizes, control groups, randomization, and other
factors, companies can ensure the validity of their test results. The more valid and repeatable the results, the
better they will hold up in the face of internal resistance, which can be especially strong when the results
challenge long-standing industry practices and conventional wisdom.
The lesson is not merely that business experimentation can lead to better ways of doing things. It can also give
companies the confidence to overturn wrongheaded conventional wisdom and the faulty business intuition that
even seasoned executives can display. And smarter decision making ultimately leads to improved performance.
Article 7.2: Kremer, H., I. Villamor and H. Aguinis (2019). Innovation leadership: Best-practice recommendations
for promoting employee creativity, voice, and knowledge sharing. Business Horizons, 62(1): 65-74.
Abstract: Innovation–—the implementation of creative ideas–—is one of the most important factors of
competitive advantage in 21st century organizations. Yet, leaders do not always encourage employee behaviors
that are critical for innovation. We integrate existing literature on the critical factors that serve as antecedents
of innovation, including employee voice and knowledge sharing, which in turn lead to creativity and innovation.
Based on existing empirical research, we offer evidencebased recommendations for managers to become
innovation leaders by: (1) developing the right group norms, (2) designing teams strategically, (3) managing
interactions with those outside the team, (4) showing support as a leader, (5) displaying organizational support,
and (6) using performance management effectively.
The critical role of innovation leadership for organizational success: Innovations leaders are change agents
(Rogers, 1995) who promote the manifestation of new ideas in a work context by creating a supportive climate
for creativity and managing the innovation process (Basadur, 2004). In light of this innovation revolution, there
is a key question that managers at all hierarchical levels should be asking: What can I do to become an
innovation leader in my organization?
On the flip side of the coin, leading companies unable or unwilling to innovate face obsolescence.
The secret sauce for innovation leadership: creativity, voice, and knowledge sharing: Next, we describe empirical
evidence regarding the critical role of employee voice and knowledge sharing in fostering creativity and
innovation.
1. Creativity and innovation: innovation does not take place in the absence of creativity. Leaders must
therefore first stage organizational contexts that promote creativity. There are two factors that lead to
creativity and then innovation: employee voice and knowledge sharing. This is supported by a substantial
body of empirical evidence, which we use in describing each of these factors.
2. Voice: Voice is a critical antecedent of creativity and innovation because it improves group decision making
and organizational learning (Enz & Schwenk, 1991), while also promoting a superior detection of errors.
When voice is not encouraged, employees are fearful ofpenalization for questioning authority, speaking up
at the wrong moment, or simply rocking the boat. In sum, voice is a key success factor needed for managers
to become innovation leaders because if new ideas are not articulated, they can hardly be implemented.
Thus, our conclusion from this body of empiricalresearch is that organizationswillbe able to implement ideas
more successfully when leaders encourage employee voice
3. Knowledge sharing: A second key success factor that leads to creativity and innovation is knowledge sharing,
which is the means by which employees get the most out of the accumulated knowledge in the organization.
Accumulated knowledge contributes to creativity and innovation, and involves organizational culture and
identity, policies, routines, systems, and also other employees. Through the use of accumulated knowledge,
knowledge sharing is positively related to ideas on,for example, how to decrease production costs and
improve team as well as firm performance
What innovation leaders do: Best-practice recommendations: Based on empirical research, we offer
evidencebased recommendations for managers, including specific actions and interventions they can implement
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Article 7.3: Coad, A., P. Nightingale, J. Stilgoe and A. Vezzani (2021). Editorial: The dark side of innovation.
Industry & Innovation, 28(1): 102-112.
Abstract: We provide a broad discussion of the dark side of innovation, before introducing the papers of the
special issue. We start with a critical reply to optimists, complementing the list of indicators showing steady
human progress with a list of indicators that show sustained deterioration (largely due to innovation). We then
outline some relevant dimensions of harmful innovation, before distinguishing between the types of harm
brought on by innovation. We conclude with an overview of the SI papers
Introduction: Innovation can have good and bad effects, and those positive and negative outcomes are typically
unevenly distributed. Choices about innovation are therefore complex and often contested, and the selection
environment that weeds out the ‘bad’ innovations is not something that can be taken for granted.
In recent years, policymakers have seemingly neglected that innovation has a direc-tion, and usually take it for
granted that ‘innovation is good’ and hence, ‘more innovation is better’. This editorial, and the special issue,
seeks to provide a bit more balance by giving space to suggestions that innovation is not always a force for good.
To do so, we discuss some dimensions we deem useful to conceptualise the link between innovation and its
possible harmful effects (section 2); we present a (non- exhaustive) list of conceptually distinct types of harms
(section 3); we then discuss three broad unanswered questions from a more practical to a more theoretical
perspective (section 4) and, finally; we conclude presenting the papers of this special issue.
Dimensions of harmful innovation:
1. Issues of scale: explorations by lead users vs the dependence of mass consumers
In this vein, the adoption of new products and technologies can cause problems due to rising demand for
key inputs, like the rapid growth in the demand for cobalt (a key input for lithium-ion batteries) causing
social problems such as corruption, environmental pollution, extreme poverty and child labour
2. End-of-product-life considerations
With new technologies, and especially technologies with long work-ing lives, these end of life costs may be
uncertain. In some instances, a new technology can reduce these costs, but in many others rising social
expectations and more stringent environmental and health regulations can substantially increase costs over
time.
3. Features vs bugs: “unintended” versus “unanticipated” consequences
Innovations can be intentionally harmful, such as for example the atomic bomb, auto-matic rifles, electric
chairs, or the ‘Spanish donkey.’ These innovations clearly cause great harm by creating new opportunities
for individuals to more effectively carry out harmful intentions.More in general, the introduction of new
technology can lead to ‘revenge effects.’ In some cases, the harm from innovation comes not from regular
use but from unanticipated accidents, such as Chernobyl. In other cases, the harm is an unintended yet
anticipated outcome that comes from proper use. This harm can be well-known or hidden. A known sideeffect of the proper use of cigarettes is lung cancer.
4. Innovation to deceive or to escape regulation
Firms may lie about the toxicity of their products. However, if this is no longer possible, they may introduce
new products that are not yet proven to be harmful (because it always takes time for the evidence to
emerge). This type of innovation to escape regulation does not address the underlying problems, but merely
delays regulation.
5. Sharing the upsides and downsides of innovation
Another issue is related to the ‘North-South’ perspective. Rich countries develop new innovations that are
applied across the world, then the rich countries notice that these innovations are toxic or harmful, and
either move on to better alternatives or develop infrastructures to deal with the waste or simply export
their waste (e.g. electronic waste). Poor countries, on the other hand, may not have the institutional
structures in place to enable them to contain the problems. Innovation is, instead, something that happens
in other places, is adapted to the institutions and culture of those places and comes from those places. Its
arrival can be very disruptive because it may not necessarily fit with the local environment, and the changes
that are required can be experienced as an imposition.
Types of harm: This section discusses various types of harm from innovation focusing on the aggregated
level of harm to society (rather than harm to single individuals) because this is the level where policy
decisions are taken
1.
2.
3.
4.
Public health risks
Environmental degradation
Harm to society
Harm to the economy