Exploring the Role of Technological Change in the Relationship

Between Strategic Innovation and Business Model Innovation:

Evidence from a Cross-Industry Multiple Case Study

Antonio Ghezzi, Jacopo Manotti, Andrea Rangone and Raffaello Balocco

Politecnico di Milano, Department of Management, Economics and Industrial Engineering,

Via Lambruschini 4B, 20156 Milan, Italy

Keywords Business Model, Business Model Innovation, Strategic Innovation, Technological Change, Lean Startup.

Abstract: Business Model Innovation (BMI) has recently caught the eye of academics and practitioners in the broad

fields of Strategy and Technology Management. However, the relationship between BMI and Strategic

Innovation (SI) remains an open issue. Thus, this study aims at investigating the relationship between SI and

BMI, focusing on the role technological change plays in it. To this end, we first propose a classification of

Technological Change types according to three dimensions: trajectory, intent and effect. Second, based on

this classification, we conduct a cross-industry multiple case study with 16 companies to understand how the

relationship between SI and BMI is mediated or triggered by the nature of Technological Change taking place,

giving rise to eight “innovation paths”. We also shed light on the key role played by different actors – top,

middle and low management and key employees – in SI and BMI, according to their level of “technological

change empowerment.

1 INTRODUCTION

The quest for technology-enabled innovation has

been influencing and permeating the very foundations

of theory, research and practice in strategy (Hamel,

1998). As environmental complexity grows and

become increasingly multifaceted, the role of

technological change has alternatively puzzled and

attracted strategists. On the one hand, by questioning

the validity of traditional approaches based purely on

strategic positioning (Porter, 2001) and jeopardizing

stable performance driven by well-established

businesses and strategies (D’Aveni and Gunther,

1994). On the other, by providing ever-renewing and

sometimes dramatic opportunities to update or create

new sources of value (Chesbrough, 2010).

Over time, diverging answers were offered to the

question of how to strategically operate in and govern

a changing environment where technology acts as a

major innovation trigger. While some scholars

investigated the effects of volatility on industry

structure and dynamics (Porter, 2001; Van Der

Zande, 2001), others focused on internalizing the

necessary resilience (Hamel and Valikangas, 2004),

dynamic capabilities (Teece et al., 1997) and

absorptive capacity (Cohen and Levithal, 1990) to

accept and adapt to volatility, while still others aimed

at stimulating and driving change to capture value as

innovators or first movers (Christensen, 1997a;

Christensen and Raynor, 2003; Kim and Mauborgne,

2005). In response to this urging issue, academics and

practitioners lately seem unanimous in claiming that

more research efforts should be directed towards an

emerging field, to some extent transversal to the

abovementioned approaches, that comprises both

Business Model (BM) design and Business Model

Innovation (BMI) (Schneider and Spieth, 2013).

BMI research arose quite abruptly from the

relatively fuzzy BM literature (Zott et al., 2011), and

such unstructured rise led to two main issues. First,

BMI inherited the relatively scarce theoretical

foundation characterizing the body of knowledge on

BM, together with the “original sin” of a still

unstructured relationship with strategy. In fact, as

shown by Schneider and Spieth (2013), BMI research

is still concentrated mostly on the identification of

prerequisites for and impacts of BMI and its

constituting processes and dynamics, but a

comprehensive theoretical background is still largely

lacking. Second, BMI research has not yet been

related to a prolific body of research that dealt with

Ghezzi, A., Manotti, J., Rangone, A. and Balocco, R.

Exploring the Role of Technological Change in the Relationship Between Strategic Innovation and Business Model Innovation: Evidence from a Cross-Industry Multiple Case Study.

DOI: 10.5220/0011717200003467

In Proceedings of the 25th International Conference on Enterprise Information Systems (ICEIS 2023) - Volume 2, pages 481-489

ISBN: 978-989-758-648-4; ISSN: 2184-4992

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

481

similar subjects of innovation and change in the last

decades: that of Strategic Innovation (SI) (Markides,

1997; Tushman and Anderson, 1997; Govindarajan

and Gupta, 2001; Govindarajan, 2005).

It can be argued that BMI and SI are inherently

related, and that this relationship is fundamentally

influenced by the nature of change affecting the

firm’s strategy (e.g. see Chesbrough, 2010; Teece,

2010). Up to now, research on this nexus has been

limited to exploratory studies in restricted industries

subjected to disruptive change (Downes and Nunes,

2013; Ghezzi et al., 2014), but a comprehensive

understanding of how different characteristics of

change impact SI and BMI is still lacking (Markides,

2006).

To fill the existing gap and push the understanding

of BMI forward, this study hence investigates the role

of technological change in the relationship between

Strategic Innovation and Business Model Innovation.

Firstly, we propose a conceptual framework that

classifies the paramount dimensions of technological

change. Based on this framework, we employ a

multiple-case study approach to investigate 16

companies in order to identify different innovation

paths, i.e. different features of the relationship among

BMI, SI and technological change. As result, we

present eight types of innovation paths that depend on

the characteristics of the technological change faced.

2 STRATEGIC INNOVATION

AND BUSINESS MODEL

INNOVATION

To understand the relationship between strategic

innovation and business model innovation, we need

to investigate the relationship between BM and

strategy. Initially, the two concepts were closely

linked (Porter, 2001), but in recent years the

distinction between them has been consolidated. In its

essence, a BM describes how an enterprise creates

and delivers value to customers, enticing them to pay

and converting payments into profits (Teece, 2010).

It is, in this sense, a novel unit of analysis that

simultaneously considers internal firm specific

factors as well as external relationships (Amit and

Zott, 2001; Schneider and Spieth, 2013). As such,

Casadesus-Masanell and Ricart (2010) argue that BM

refers to the way the firm operates and creates value,

while strategy refers to the choice of the BM to

compete. BM, thus, becomes a valuable tool for

developing and implementing strategy: a mechanism

to both map the business in static conditions and

describe the internal strategic context during change

(Hacklin and Wallnöfer, 2012).

If BM is a tool to develop and implement strategy,

it is arguable that SI and business model innovation

(BMI) are closely related. Kim and Mauborgne

(1997), for instance, praised the benefits of value

innovation, a new strategic logic which refers to

fundamentally changing the basis of a business’

dominant value proposition in order to create and

dominate new competitive landscapes. Similarly,

Hamel (1998) proclaimed that competitive advantage

in the dynamic environment of the 21

century would

reside in “changing the rules of the game”, that is,

performing a non-linear BMI.

Both Kim and Mauborgne (1997) and Hamel

(1998) were writing in the context of SI

(Govindarajan and Gupta, 2001; Charitou and

Markides, 2003), a research stream in management

theory that aimed at developing firms’ capabilities to

continuously generate innovations as a competitive

response in changing environments. SI is

alternatively defined as the strategic process

responding to or triggering change (Martinsons,

1993; Markides, 2006), the innovation of strategy in

itself (Hamel, 1998), or innovation with strategic

impact (e.g., see Afuah, 2009).

Building on the nature of the relationship between

BM and strategy, it can be posited that BMI serves as

a means to operationalize SI endeavors. However, not

every strategic innovation is the same.. Ghezzi et al.

(2014), for instance, found evidence that in some

cases, BMI can lead to emergent SI rather than the

other way around. Thus, it becomes important to

investigate the role of technological change in the

relationship between SI and BMI.

3 THE ROLE OF

TECHNOLOGICAL CHANGE

IN THE SI-BMI RELATIONSHIP

In strategy research, the nature and classification of

technological change vary. As Drucker (1969) states,

changes can take place in the form of technological

environment uncertainties, due to the rise of new

technologies (“technological discontinuity”) that

affects the industry structure. Additionally,

discontinuities can occur in competences and

resources necessary for designing and producing

products; changes in the product itself as physical

changes; and price/performance changes (Ehrnberg,

1995).

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Another characterization of environmentally-

driven change is found in Miller (1985), who describe

changing environments in terms of dynamism (that is,

the rate of change in customers’ expectations,

technologies, or competitors’ responses). However,

technological change not only originates in the

external environment. Instead, it can also be triggered

inside the firm, by emerging phenomena within the

internal environment (Ghezzi et al., 2015). Such

endogenous discontinuities are often linked to gaps in

the “work setting”, “tasks” or “relations” (Watson-

Manheim et al., 2002). Indeed, technological change

within an enterprise can manifest itself as either a

prominent or a local modification in processes,

practices or routines, or a variation in products (by

creating different outputs due to an innovation)

(Anderson and Tushman, 1990). Interestingly, such

internal phenomena may take place unintentionally,

due to the risk component which resides in the

planning processes of every enterprise and makes it

impossible to achieve perfect forecasting (Schreyögg

and Steinmann, 1987).

Intent is indeed another key dimension that

characterizes technological change and its influence

on strategy and BM. The discussion on the explicit or

implicit intention to change manifested by a

company’s top management can be borrowed from

the literature on the strategy making process, which

contrasts a deliberate approach to strategy making

and strategic planning (e.g. see Armstrong, 1982;

Lorange, 1980; Chermack et al., 2001) to an emergent

(and possibly bottom-up) process made of a set of

informal strategic decisions (Mintzberg, 1994;

Christensen, 1997b).

Considering that BMI is the operationalization of

strategy making process (Shafer et al., 2005;

Casadesus-Masanell and Ricart, 2010), BMI can

therefore be indirectly influenced by technological

change factors, which impact or modify the BM

constituting building blocks or parameters (e.g.

Ghezzi et al., 2014). Therefore, depending on its

characteristics, change may have different forms of

influence on Strategy Innovation and BMI.

The way technological change phenomena

manifest varies according to a set of key features and

characteristics that we bring back to three

dimensions: trajectory; intent; and effect (Table 1).

Table 1: Three classification dimensions of Technological

Change.

Dimension Alternatives

Trajectory

(e.g. Miller, 1985; Schreyögg and

Steinmann, 1987; Watson-Manheim et

al., 2002; Anderson and Tushman, 1990)

Endogenous

Exogenous

Intent

(e.g. Lorange, 1980; Armstrong, 1982;

intzber

, 1994; Christensen, 1997b

)

Deliberate

Emerging

Effect

(Drucker, 1969; Miller 1985; Ehrnberg,

1995; Bessant et al., 2005; Ghezzi et al.,

2014)

Continuous

Discontinuous

The three classifications dimensions can be presented

in different combinations of their alternatives in terms

of continuous-discontinous, exogeneity-endogeneity,

emerging-deliberate, resulting in a set of 8

configurations. Based on them, , one research

question (RQ1) rises up: how does the typology of

technological change influence the relationship

between SI and BMI? We argue that technological

change may act as an influencer – either a mediator

or a trigger – of the relationship between SI and BMI.

In summation, we suggest that the relationship

between SI and BMI may depend on the direction

(trajectory), causality (intent) and intensity (effect) of

technological change that takes place in a specific

context.

4 RESEARCH METHOD

For this study, we adopted an empirical qualitative

multiple-case study research (Yin, 2009). Qualitative

multiple-case study is useful for theory building

based on extensive field analysis, when researchers

need to understand how a given phenomenon happens

(Yin, 2009; Eisenhardt and Graebner, 2007).

The cases were selected by means of theoretical

sampling (Eisenhardt and Graebner, 2007), where the

companies included in the theoretical sample were

drawn from a cross-industry database created by

researchers involved in a two-year international

research project on firms undergoing technology-

enabled BMI. Due to the explorative nature of the

topic, the research favoured depth of analysis over

width, and a limited population of 45 firms from

different industries and countries was selected. After

a preliminary contact, 28 companies expressed

interest in participating, and 22 were ultimately

selected due to the inability to gather necessary

information from 6 of them. Through cross-case

analysis, some cases with similar dynamics were

Exploring the Role of Technological Change in the Relationship Between Strategic Innovation and Business Model Innovation: Evidence

from a Cross-Industry Multiple Case Study

483

excluded, resulting in the final sample size of 16

companies. The final sample included at least two

cases for each of the eight configurations. For data

collection, we followed Yin (2009), employing a

descriptive case study method based on 88 semi-

structured interviews and documental analysis with

57 informants during a period of 14 months. Each

meeting had an average length of 1h 42 minutes.

The need for assessing SI and BMI processes,

nature of technological change and the sequence of

relationships linking them led to the adoption of an

“embedded” case study (Yin, 2009), with multiple

units of analysis, related to: (i) technological change

(ii) strategic innovation; and (iii) BMI.

The reference framework selected to assess BMI

is that proposed by Osterwalder and Pigneur (2010),

which considers nine parameters a BM is made of:

(BMi) Value Proposition; (BMii) Customer

Segments; (BMiii) Channels; (BMiv) Customer

Relationship; (BMv) Key Activities; (BMvi) Key

Resources; (BMvii) Key Partners; (BMviii) Revenue

Streams; and (BMix) Cost Structure. Such framework

is widely adopted and employed both by practitioners

and academics (e.g., see Chesbrough, 2010). For data

analysis, we used the Technological Change

configurations and the details collected during the

interviews about the sequence in which BMI occurs

considering the SI process and the need or

opportunity of change. We codified interviewees’

statements and comments into the three units of

analysis; thus, we performed qualitative content

analysis based on the chronological perspective of the

technological change process for each company.

5 RESULTS

Next, we discuss the cases and the observed

innovation path that describes the relationship

between strategy and BMI when considering the role

of each type of technological change.

Type 1: Exogenous, Deliberate and Continuous

Change and the First Innovation Path

In both cases A and B, change had an outside-in

thrust, originating from the external environment and

influencing firms’ strategy and BM. Notwithstanding

its external origin, change was deliberately

interiorized by top managers, and a SI process was

hence triggered to include the features and outcome

of change within firms’ strategy. In turn, SI was

concretized and executed through BMI, and drove a

redesign of one or more dimensions in the current

BM. In this type, the continuous trait of change

determines incremental variations of those BM

dimensions affected by innovation. Consequently,

our cases A and B suggest that change was hence the

trigger of a deliberate SI, which later reflected top-

down on BMI and incremental variations of the

performance of the current BM.

Type 2: Exogenous, Deliberate and Discontinuous

Change

In both cases C and D, change had an outside-in

thrust, originating from the external environment and

influencing firms’ strategy and BM. Notwithstanding

its external origin, change was deliberately

interiorized by top managers, and a SI process was

triggered to include the features and outcome of

change within the firms’ strategy. In turn, SI was

concretized and executed through BMI, and drove a

redesign of several dimensions in the current BM.

The discontinuous trait of change determined radical

variations of those BM dimensions affected by

innovation. Cases from Companies C and D suggest

that in this type, change is the trigger of deliberate SI,

which later on reflects top-down on BMI and radical

variations of the current BM.

Type 3: Endogenous, Deliberate and Continuous

Change

In these two cases E and F, the rise of internal

resources, competencies and know-how was

embraced within a deliberate and continuous strategic

innovation and BMI represents the execution of such

deliberate strategy. Consequently, change was the

effect of a deliberate strategic decision made by the

top management, who, by means of SI, aimed at

modifying the current strategy, BM and performance.

Therefore, change determined by SI followed an

inside-out trajectory, stemming from inbound

processes and dynamics and later reflecting on the

firms’ BM, and being executed through BMI. The

continuous trait of change determined incremental

variations of the performance of those BM

dimensions affected by innovation. Change was

hence the mediator between deliberate incremental SI

and its top-down concretization through incremental

BMI.

Type 4: Endogenous, Deliberate and Discontinuous

Change

In both cases G and H, change was the effect of a

deliberate strategic decision made by top

management, who, by means of SI, aimed at

modifying the current strategy, BM and performance.

Thus, SI generated change according to an inside-out

trajectory, stemming from inbound processes and

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dynamics and later reflecting on the firms’ BM, and

being executed through BMI. The discontinuous trait

of change determined radical variations of those BM

dimensions affected by innovation. Consequently,

this particular type of change was the mediator

between a deliberate radical SI and its top-down

concretization through a radical BMI.

Type 5: Exogenous, Emerging and Continuous

Change

In these cases I and J, change had an outside-in thrust,

originating from the external environment and

influencing firms’ strategy and BM. Change

propagates and spreads in the firm in an emerging and

unstructured fashion, not immediately reflected in a

variation of the overall strategy, but rather being

absorbed locally in one or more BM dimensions that

represent the strategy’s implementation. Emerging

variations in the BM characterize a BMI. The

continuous trait of change determined incremental

variations of those BM dimensions affected by

innovation. Following a bottom-up diffusion process,

BMI is later caught up by and formalized within the

overall strategy through SI. Change was hence the

trigger of an emerging incremental BMI, which then

propagated bottom-up to cause an incremental update

of the firm’s Strategy through SI.

Type 6: Exogenous, Emerging and Discontinuous

Change

In these two cases K and L, change had an outside-in

thrust, originating from the external environment and

influencing firms’ strategy and BM. Change

propagated in the firm in an emerging and

unstructured fashion, not immediately reflected in a

variation of the overall strategy, but rather being

absorbed locally in one or more BM dimensions that

represented the strategy implementation. The

emerging variations in the BM caused a subsequent

BMI, as the other BM dimensions must be adapted to

cope with localized evolutions. The discontinuous

trait of change determined radical variations of those

BM dimensions affected by innovation. Following a

bottom-up diffusion process, BMI was later caught up

by and formalized within the overall strategy through

SI. Change was hence the trigger of an emerging

radical BMI, which then propagated bottom-up to

cause a radical update of the firm’s Strategy through

SI.

Type 7: Endogenous, Emerging and Continuous

Change

The type of change appearing in cases M and N had

the effect of implicit, unstructured or local

modification of the firms’ current BM. Such change

propagated and spread in an emerging and

unstructured fashion, not immediately reflected in a

variation of the overall strategy, but rather being

absorbed locally in one or more BM dimensions.

Emerging variations in the BM characterize a BMI.

The continuous trait of change determined

incremental variations of those localized BM

dimensions affected by innovation. Following a

bottom-up diffusion process, BMI was later caught up

by and formalized within the overall strategy through

SI. Thus, change was the mediator between an

emerging incremental BMI and SI that causes an

incremental bottom-up update of the firms’ strategies.

Type 8: Endogenous, Emerging and Discontinuous

Change

Change, in cases O and P, was the effect of an

implicit, unstructured or local modification of the

firms’ current BM. Change propagated in an

emerging and unstructured fashion, not immediately

reflected in a variation of the overall strategy, but

rather being absorbed locally in one or more BM

dimensions. The emerging variations in the BM cause

a subsequent BMI. The discontinuous trait of change

determined radical variations of those BM

dimensions affected by innovation. Following a

bottom-up diffusion process, BMI is later caught up

by and formalized within the overall strategy through

SI. Change was hence the mediator between an

emerging radical BMI and SI that caused a radical

bottom-up update of the firms’ strategy.

6 DISCUSSION AND

CONCLUSIONS

The proposals and findings presented in this study

touch upon and relate two key themes in the research

stream on BM, strategy and technology: (i) the

relationship between SI and BMI and the nature of

technological change’s influence on it; and (ii) the

actors and roles in technology-enabled BMI as a

process.

First, this study focuses on clarifying the

relationship existing between BMI and SI. The link

between BM and technological change was already

postulated in several works (Lindgardt et al., 2009;

Teece, 2010; Chesbrough 2010; Casadesus-Masanell

and Ricart, 2010), whose main findings claim that: (i)

BM and BMI research still suffers from fuzzy

definitions and lack of a common theoretical frame;

(ii) BM is closely related to business strategy, in the

Exploring the Role of Technological Change in the Relationship Between Strategic Innovation and Business Model Innovation: Evidence

from a Cross-Industry Multiple Case Study

485

sense that it acts as strategy execution; and (iii)

entrepreneurs and managers innovate BMs by means

of technological experimentation and learning,

although the efficient development and

implementation of new business models in corporate

practice is a complex process.

Although previous studies pointed in the same

direction, they showed a largely conceptual approach

to the problem, and mostly focused on the dyadic

relationships strategy-BM and BM-technological

change only. Our study’s contribution refers to the

investigation of a wide multiple case study which

reports and compares findings from diverse industries

and allows to ground on empirical evidence the claim

that strategy and BMI are closely coupled. We

establish a more formal and systematic relationship

between these concepts, thus confirming and

extending the conceptual work from Teece (2010).

More specifically, we extend the insightful proposals

from Casadesus-Masanell and Ricart (2010) and

Richardson (2008) to their natural (but still implicit)

consequences: being the BM the way a firm executes

its strategy, we claim that Business Model Innovation

is the concretization of Strategic Innovation. Indeed,

as our cases show, SI choices affect one or more BM

parameters, ultimately determining BMI – or

conversely, BMI will eventually lead to SI. Business

Model Innovation is hence “Strategic Innovation in

action”. This finding suggests a transitivity in the

BM-Strategy and BMI-SI relationships which helps

connecting the so far parallel streams on BMI and

Strategic Innovation. In addition to consolidating and

extending the BMI-SI relationship, our study makes

one key step further, by finding that the nature and

characteristics of technological change significantly

matters in such relationship. Indeed, positioning the

cases in the Technological Change Types Matrix

shows that technological change acts as an influencer

– either a mediator or a trigger – of the relationship

between SI and BMI.

Since change is the essence of BMI and SI, both

their origin and outcome, and acts as the fil rouge that

connects SI with its execution through BMI,

including the nature of change in the equation helps

shedding light on the idea that a relationship exists,

though its direction and sequence is not

predetermined. The relationship between SI and BMI

depends, in its direction (trajectory), causality (intent)

and intensity (effect), on the type of technological

change in place.

Our framework which classifies the 16 cases on

the basis of eight change types gives rise to eight

different “innovation paths” for the relationship

between SI, BMI and technological change itself.

This finding relates to the second key theme that

concerns the actors and roles in BMI and SI as a

process. We find that the dimension of change intent

plays a fundamental role in shaping the causality of

the SI-BMI relationship. The comparison between the

eight cases belonging to change types 1 to 4, where a

deliberate intent characterized innovation, with cases

in change types 5 to 8, where intent was emerging,

shows that in the former innovation paths SI

determines BMI, where in the latter it is BMI that

triggers SI.

Hence, two different streams of innovation in

strategy seem to exist: (i) the formal, top-down and

overarching one, which aims at innovating the firm’s

explicit mission, vision and strategic goals

(innovation paths 1 to 4); and (ii) the rather informal,

bottom-up, possibly local and undercurrent one,

which emergently changes the way a firm operates in

its attempt to create value and reap a share of it

(innovation paths 5 to 8).

The first stream clearly refers to the traditional

research stream on the strategy making process

(Armstrong, 1982), with the addition that a change in

strategy eventually reflects on a change in the BM

(Casadesus-Masanell and Ricart, 2010; Johnson et al.,

2008). The second stream contributes to the

discussion on “business model lifecycle” (Morris et

al., 2005) and “experimentation” (Lindgardt et al.

2009; Chesbrough, 2010), particularly in the context

of strategic experimentation (Govindarajan and

Trimble, 2005). According to Morris et al. (2005), the

business model lifecycle consists on: an initial period

during which the model is fairly informal or implicit;

a process of trial and error where number of core

decisions are made that constraint the directions in

which it can evolve; and a final step where a fairly

definitive, formal model is established. Subsequently,

adjustments are made and on-going experiments are

undertaken. Chesbrough (2010) wrote that companies

must adopt an effectual attitude toward business

model experimentation. Thanks to effectuation

(Sarasvathy, 2008) they can create actions based on

the initial results of experiments, generating new data

which may point towards previously latent

opportunity.

The four change types related to an emergent

intent are examples of these BMI dynamics, with a

significant addition referring to the role of managerial

leadership in the survival of emerging BMI resulting

from experimenting. If it is true that new ideas and

opportunity discover can arise from everywhere in the

company, it is also proved that without the right

authority mobilized for change, it will not take place

(Hamel, 1998). Mansfield and Fourie (2003) state that

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developing and implementing new or changed

business models requires entrepreneurial flair and

careful management of risk. The discussion is

revisited in Chesbrough (2007), who underlines the

“business model innovation leadership gap” existing

in many organizations: no one in the organization has

both the authority and the capability to innovate

business models. Since it takes a lot of time to

develop business model experiments, obtain clear

results, interpret and understand the results, and then

carry out a broad deployment of those results, top

managers usually represent a barrier to innovation.

Indeed, top managers normally reach their level of

responsibility by executing within the current

business model, so that the model is familiar and

reassuring to them (Chesbrough, 2007). It is almost

like an opportunistic behavior that immobilizes

company‘s practices and prevents business models to

adapt to fast changing environmental conditions. An

organization needs to identify internal leaders for

business model change (Chesbrough, 2010) and give

senior managers the resources and authority to define

and launch business model experiments (Chesbrough,

2007).

Our study contends that it is true that technology-

enabled innovation will not take place at a planned

formal strategy level without a top-down deliberate

approval, though it will survive and live at an

operational strategy level, and may drive performance

change even before the overarching strategy catches

up. To different extents, this is the case for the eight

companies who followed innovation paths 5 to 8,

where innovation was led by middle/low

management and employees with a strong grip on

BM’s operational execution, thanks to specific

technological skills and know how. This is to some

extent consistent with the recent notion of “big bang

disruption” and “undisciplined strategy” posited by

Downes and Nunes (2013) where technology-enabled

innovations may not be led by a strategy and shared

by a top manager, since change may not require a

budget approval and may be based on experimenting

and combining different resources and asset, either

internal (see cases M, N, O and P) or external (see

cases I, J, K and L).

Our study shows that BMI may survive the lack

of supervision and strategic commitment by the top

management, being primarily led by line managers

and employees invested in experimentation on

operational level. This claim may attenuate the risk of

encountering top managers that impair rather than

enable BMI; also, it sheds light on the need to focus

the attention of practitioners on the “technological

change empowerment” or strategic independence

they wish to vest the line management and employees

with. Such technological empowerment should be

properly balanced with an ability to supervise and

eventually consolidate BMI, thus avoiding any

strategic inconsistencies deriving from a bottom-up

approach.

Value for practitioners is equally important, since

this study provides a set of tools to: (i) categorize

technological change; (ii) relate technological change

types to SI and BMI, and map the “innovation path”

a firm has – explicitly or implicitly – undertaken; and

(iii) disclosing the strategic role of technological

change empowerment assigned to different actors.

Like all studies attempting to frame reality in a

model, this work is not without limitations, deriving

from: any observer bias in the activities of case data

gathering and analysis; and the possible information

loss determined by case selection. Although the

sound methodologies and the use of a wide cross-

industry sample attenuate such limitations, a

validation of these finding through quantitative

analyses on a larger sample should be the objective of

future research. Other opportunities for future

research could: relate to the investigation of how firm

size can influence the SI-BMI relationship and the

chance to actually trigger BMI without a deliberate

strategic commitment; define managerial guidelines

to confer technological change empowerment, by

recognizing it as a possible source of BMI; and assess

the opportunities and risks deriving from a distributed

strategic independence allowing managers and

employees to leverage their technological skills

endowment, which could lead to local or contingent

approaches (a sort of uncontrolled explosion of case-

specific BMs) possibly diverging from the

institutional strategic intent.

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