Paper to be presented at the DRUID 2012

on

June 19 to June 21

at

CBS, Copenhagen, Denmark,

Mind the Gap: Adapting and Reorienting Organizational ArchitecturesFederica Ceci

University G.d'AnnunzioDEA

f.ceci@unich.it

Francesca MasciarelliUniversity G.d'Annunzio

DEAf.masciarelli@unich.it

Andrea Prencipe

University 'G. d'Annunzio'Department of Management and Business Administration

a.prencipe@unich.it

AbstractThe study of organizational architecture builds upon the analysis of the different answers provided by organizations toincrease the fit with their external environment. Investigating such theme, scholars emphasize the evolutionary nature offirms in terms of adaptation, flexibility, evolution and decomposability: firms combine and recombine elements thatcompose its architecture, modifying them in a number of different ways. In the present work we examined how theorganization modifies its architecture in response to environmental feedback, measured in terms of performance gap. Ina study of 755 organizations, we found that, depending on the presence of a performance gap, the organization decideswhether to maintain its current architecture or to modify it. Interestingly, the extension of the performance gap affects themagnitude of organizational architectural change: on the basis of the extension of the performance gap, the organization

will implement either minor or major modifications in its architecture.

Jelcodes:O33,L22

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Mind the Gap:

Adapting and Reorienting Organizational Architectures

Federica Ceci*

Francesca Masciarelli*

Andrea Prencipe*+

*Dipartimento di Economia Aziendale – Università G. d’Annunzio di Chieti-Pescara

+SPRU, University of Sussex – UK

Abstract

The study of organizational architecture builds upon the analysis of the different answers

provided by organizations to increase the fit with their external environment. Investigating such

theme, scholars emphasize the evolutionary nature of organizations in terms of adaptation,

flexibility, evolution and decomposability: organizations combine and recombine elements that

compose their architecture, modifying them in a number of different ways. In the present work

we examine how organizations modify their architecture in response to environmental feedback,

measured in terms of performance gap. In a study of 755 organizations, we find that, depending

on the presence of a performance gap, organizations decide whether to maintain their current

architecture or to modify it. Interestingly, the extension of the performance gap affects the

magnitude of organizational architectural change: on the basis of the extension of the

performance gap, organizations will implement either minor or major modifications in their

architecture.

Keywords: organizational change; adaptation; reorientation; performance gap.

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1. Introduction

Organizations are in a continuous search to increase the fit with their external environment.

In this search, they combine and recombine elements that compose their architectures, modifying

them in a number of different ways (Lawrence & Lorsch, 1986; Milgrom & Roberts, 1995;

Siggelkow, 2002; Zott & Amit, 2008). Evaluating their performance in comparison with the

external context, organizations process information obtaining feedback on their behavior (Greve,

1998). Several studies have highlighted the importance of environmental feedback as a key

driver of organizational change although each organization finds a unique way to address

external stimuli (Bensaou & Venkatraman, 1995; Ceci & Masini, 2011; Dennis & Meredith,

2000). The existence of a link between environmental feedback and organizational change is

widely accepted but scale and scope of organizational changes are partially unknown. In order to

fill this gap, this paper explores how organizations modify their architecture in response to

environmental feedback.

It is known that organizations are adverse towards risk (Greve, 1998; Greve & Taylor,

2000), but they reduce aversion when they fail to reach goals or aspirations (Greve, 1998). In

defining their aspirations, organizations are conditioned by the performance obtained in their

past experiences and by the performance of similar organizations. The higher the gap with the

past performance or with the performance of similar organizations, the lower will be their

aversion toward risk (Grinyer & Mckiernan, 1990; Kahneman & Tversky, 1979; Vissa, Greve, &

Chen, 2010). The existence of such gaps fosters organizations to undertake architectural changes

by selecting one of the following strategies: (i) playing the old game, i.e. the organization does

not change anything, keeping its old configuration; (ii) playing an incomplete game, i.e. the

organization changes single elements in its system; (iii) playing a new game, i.e. the organization

changes a whole range of its elements (Siggelkow, 2001).

The following examples illustrate the implications of such decisional process. To explain

the incomplete game situation, Siggelkow (2001) reports the case of the American automobile

industry that observed a gap with the performance of their Japanese competitors. By copying

only a few elements of the Japanese production system, the American automobile industry

played an incomplete game for many years (Hayes & Iuikumar, 1988; Siggelkow, 2001: 842).

One of the most famous cases of successful “playing a new game” strategy is the transition

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toward services operated by IBM at the beginning of the 90s. To face the increasing competition

and losses in revenues, the CEO Louis Gerstner imposed changes in strategy, including

international dimension, role of IT and new technologies and in the internal configurations such

as behavioral and cultural aspects. Every aspect of the old architecture has been modified and the

result was a completely different company (Bramante, Frank, & Dolan, 2010; Gerstner, 2002;

Lichtenthal & Copulsky, 1993). Undertaking such restructuration is undoubtedly painful and

risky for the organization. So far, it is not clear what are the forces that push organizations

towards such uncertain path. This paper addresses this issue refining and extending our

comprehension of organizational change. We draw upon insights from prior studies that have

examined the concept of organizational architecture (Gulati & Puranam, 2009; Mendelson, 2000)

and studies on performance gap (Greve, 1998). From studies on organizational architecture, we

construct an original measure of organizational architecture while from studies on performance,

we infer how organizations define their aspirational levels.

Empirically, this paper uses an original database obtained by merging two datasets: data

are based on two waves of a large survey conducted by Unicredit, an Italian bank group. Results

show that when performance feedback presents a minor gap to be filled, organizations are likely

to implement minor changes to their architecture. On the contrary, organizations implement

major modifications to overcome a large performance gap. In these two cases (i.e. minor and

major gap), scale and scope of change differ and a discrete model, where modifications of

organizational architecture are not seen in a continuum, is more appropriate in describing

organization’s decisions.

2. Theoretical background

2.1. Understanding organizational architecture

Organizations are complex systems, which include several interrelated elements: they

perform complex tasks that cannot be carried out by a fully integral, entirely interdependent

organization. To successfully operate in markets, organizations decompose those tasks

generating an organizational structure composed by different elements. Based on this reasoning,

many scholars consider organizations as an architecture of different elements and they explore

their structure focusing on their evolutionary nature in terms of adaptation, flexibility, evolution

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and decomposability, as articulated by Simon (1969) (Dosi & Grazzi, 2006; Ethiraj & Levinthal,

2004; Fixson & Park, 2008; Jacobides, 2006; Mendelson, 2000)..

Makadok (2001) suggested that elements that compose organizational architecture should

be unique, imperfectly imitable, and aimed to improve the productivity of organizations. Relying

on the contingency approach, we regard as true the idea that superior performance can be

achieved only when elements of organizational architecture are combined coherently to match

the characteristics of the environment in which organization operates (Drazin & Van De Ven,

1985; Duncan, 1972; Venkatraman, 1989). Organizational architecture is composed by the

interplay between organizational elements and changes in organizational architecture are

determined by a modification in its elements.

Our understanding of organizational architecture builds on the works done by Gulati and

Puranam (2009) and by Mendelson (2000). In fact, Mendelson (2000) identified a set of core

elements of organizational architecture looking at how information is processed and distributed

within the organization. By defining organization as an information-processing system that

assimilates information from the external context and match it with internal information, he

proposed an organizational architecture based on information awareness. Consistently with

Mendelson (2000), this study define organizational architecture decomposing organizations in a

set of architectural elements taking into account how information and knowledge are transferred

and processed within the organization. On the other hand, Gulati and Puranam (2009) explored

organizational architecture focusing on changes between formal organization – i.e. the normative

social system design by managers – and informal organization – i.e. the patterns of social

interaction that emerge within an organization. In line with Gulati and Puranam (2009), we look

at organizational architecture in terms of combination of organization’s choices. However,

differently from Gulati and Puranam (2009), who emphasized the duality between formal and

informal organization, we focus on formal organization elements. Differently from the informal

organization elements, the formal ones can be changed relatively rapidly (Lamont, Williams, &

Hoffman, 1994). This enables to explore how organization responds to environmental changes in

the short term.

2.2. Organizational change, environmental feedback and external fit

Organization theory provides different perspectives to organizational change. In particular,

population ecologists emphasized upon peremptory environmental determinism (e.g. Hannah &

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Freeman, 1984): building on Stinchcombe (1965), Hannan and Freeman (1984) claim that

organizations are often inert for different attrition forces. Those attrition forces include the

cognitive lock-in produced by the initial mode of operating or imprinting and by the lack of

search for information on relevant contingencies to which it may be worth to adapt. Informed by

contingency theory ideas, Zajac et al. (2000) and Siggelkow (2001) discuss the effectiveness of

organizational change. From these studies it is possible to capture the idea that a straightforward

application of contingency theory contemplates the possibility of a beneficial inertia, or stability.

When environmental contingencies change, organizations should modify accordingly, but when

the environmental contingencies are relatively stable, it might be convenient for the

organizations to stay stable as well (McCarthy, Lawrence, Wixted, & Gordon, 2010). This

suggests, as logical consequence, that, under some circumstances, organizational stability can be

beneficial (Tushman & Romanelli, 1985). Prencipe and Grandori (2008: 235) name this

organizational behavior “contingently effective invariance”, arguing that the reasons for stability

is not the continuation of a state, but the absence in the organizations’ environment of threats that

are contingently effective. On the contrary, when the organizations perceive the presence of

threats in the environment they are likely to develop a new definition of the internal

configuration that could ensure the permanence of external fit (Siggelkow, 2001). Therefore, the

decision to change the organizational architecture is highly influenced by the perception of

possible threats in the organizations’ environment.

Referring to the stream of literature that has supported the importance of cognition in

explaining organizational stability (Garud & Rappa, 1994), we draw some insights on how to

specify threats we expect determine an organizational change. Managers are bounded rational

and rely on simplified representations of the world to process information (March, Guetzkow, &

Simon, 1958; March, 1988; Simon, 1955). Cognitive representations are considered relevant to

explain the organizational behavior, and ultimately, the propensity to change (Tripsas & Gavetti,

2000). The borderline between perceived success and failure is called “aspiration level” (Greve,

1998; Lopes, 1987; Schneider, 1992). An aspiration level has been described as a “reference

point that is psychologically neutral” (Kameda & Davis, 1990: 56) or as "the smallest outcome

that would be deemed satisfactory by the decision maker" (Schneider, 1992: 1053). Kiesler and

Sproull (1982) explain that cognitive representations are typically based on historical experience

as opposed to current situation. This suggests that aspiration levels depend on organizational

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history and the attention patterns of their members.

Greve (1998) suggests that organizations process environmental feedback by comparing

their performance with the performance of other organizations operating in the same industry

and by comparing their current performance with their past performance. Therefore,

organizations use two aspiration levels: the social aspiration level, which is obtained from a

comparison with competitors; and a historical aspiration level, which is obtained from a

comparison with the organization past performance (Cyert & March, 1963; Wood, 1989).

Organizations, as individuals, are provided to be averse to risk since risk choices put them in

front of many possible unpredictable outcomes and pose the treat of very poor outcomes.

Organizations appear resistant to change, but, in some circumstances, they modify into forms

remarkably different from the original. As pointed out by Greve (1998), organizations reduce

their aversion towards risk when they fail to reach their goal or aspiration. The underlying

process is one in which the organization is conditioned through the performance obtained in the

past experiential learning (Day & Groves, 1975) and through the performance of similar

organizations. The social comparison theory suggests that aspiration level are related to the

comparison with the performance of similar others (Cyert & March, 1963; Festinger, 1954). As

individuals, organizations do not evaluate their abilities by comparison with others who are too

divergent from them. If other’s abilities are too far, either above or below, it is not possible to

evaluate organizations’ abilities accurately with comparisons with them. Consequently, the

organization will chose for comparison other organizations that present similar characteristics.

Also, theory on aspiration analyzes the performance history of the organization itself (Cyert &

March, 1963; Greve, 2002; Levinthal & March, 1993), comparing the current level of

performance with the previous ones. Environmental feedback is, therefore, processed by the

organizations in terms of performance gap with their aspirational levels.

3. Hypotheses development

Organizations align and re-align their architectures to the environment: we posit that

organizations process environmental feedback by defining an aspirational level that is obtained

by comparing the current level of performance with (a) previous performance and (b)

performance of organizations operating in the same industry (Cyert & March, 1963). We expect

changes in organizational architecture be influenced by the organization’s position in relation to

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those two aspiration levels. When the organization perceives the presence of a gap between its

performance and social and historical aspirational level implements change in its organizational

architecture. This leads to Hypothesis 1:

Hypothesis 1:the presence of a performance gap increases the likelihood that the

organization will modify its architecture.

As argued above, as long as the organization environment does not present any threats,

stability is found to be beneficial (Tushman & Romanelli, 1985). However, when organizations

perceive the presence of threats in their environments, stability becomes a liability (Siggelkow,

2001). Organizations need to maintain co-alignment with changing contingencies in their

environments (Kraatz & Zajac, 2001). Building on literature on individual and organizational

risk taking, Greve (1998) explains that the organizations’ decision to undertake strategies that

involves a high degree of risk depends on the context of the choice (Lopes, 1987; Thaler &

Johnson, 1990). In any organizational context, managers take fewer risks when performance

exceeds their goals (Singh, 1986). On the contrary, high organizational risk taking is related to

low performance relative to aspirations (Bowman, 1982; Bromiley, 1991; Grinyer & Mckiernan,

1990). Managers are available to assume the risk of change when they perceive the presence of a

performance gap (Chattopadhyay, Glick, & Huber, 2001). Therefore, we can identify three

different situations, according to the extension of the performance gap highlighted by the

organizations.

The decision process that organizations follow when implementing organizational

architectural changes is articulated in two steps: (i) the organization decides whether to change

its organizational architecture or not, adopting ongoing changes to its organizational architectural

elements; (ii) the organization decide whether to adopt minor or major changes to its

organizational architecture. In the first case both social and historical aspirational levels are in

line with the organization’s actual performance. Ongoing changes are applied to single

organization architectural elements and the scale of change is very low. Their scope is to adjust

the organization architectural elements to make them evolve with the naturally occurring

environmental changes (Feldman, 2000; Tsoukas & Chia, 2002). An empirical example is

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represented by the upgrade of ICT architecture that must be periodically revised to be up-to-date

with the technological innovation occurring in the field. In the second case, we can detect a

misalignment with aspirational levels, i.e. social or historical levels are not in line with

organization performance: in such situations, organizations are asked to fit the gap and the extent

of the change is proportioned with the dimension of the gap, as we explain as follows.

3.1. Adaptation strategy

In the case of a partial misalignment with aspirational levels either social or historical level

is not in line with organization performance. The limited performance gap makes the expected

outcomes generally good and, in line with the previous reasoning, managers are risk adverse.

The scale of changes is low and it includes few organizational elements. In such situations,

organizations tend to imitate other companies in their comparison group or to compare their

organizational choices with their past experience. This reduces the riskiness associated with

changes and it legitimate organizations to imitate the prevalent behavior. This is a way to resolve

uncertainty and gaining legitimacy; the imitation of organizational structures is driven by norms

of rationality (Meyer & Rowan, 1977) and uncertainty (Di Maggio & Powell, 1983). However,

unusual and innovative practices are rarely adopted (Massini, Lewin, & Greve, 2005). The scope

is to solve a locally sourced problem; e.g. decreasing the cost of production trough the use of

offshoring. We observe actions aiming at modify the structure of a single architectural element,

as the international dimension in the cited example. These actions respond to the need of solving

a problem that involves a limited number of actor and not the whole organization. The search for

a local solution is preferred due to lower risks associated with it. In fact, risks connected with the

adjustment procedure are generally lower and this path is selected by those organization that

experienced small gaps between the effective performance and their aspirational level. An

example of minor changes is the one of Daehan Steel, a Korean organization that undertook a

business transformation project to enable the future growth of the company as "a total steel

solution provider" (IBM, 2010). In this case, the organization aimed to fill the gap with

competitors, not experiencing any major losses in its revenues, compared to the past. Daehan

Steel implemented a complete modification of IT architecture (contract management system,

standard cost management, supply chain management, operation system, ERP system, pricing

strategy planning and diagnosis of Information Technology operations), required to facilitate the

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growth of Daehan Steel not only in Korea but in the global marketplace. This line of reasoning

leaves to our second hypothesis.

Hypothesis 2: the presence of minor performance gap increases the likelihood that the

organization will adapt to the environment through small architectural changes

3.2. Reorientation strategy

Organizations may find themselves to deal with a misalignment of both social and

historical aspirational levels. Those organizations that experience a major gap in their

performance do lose competitive grounds in relation with peers and with their own past

performance. To fill the gap, organizations are called to pursue major modifications in their

architecture that imply higher risk (March & Shapira, 1387). This is consistent with Yasai-

Ardekani (1989) who argue that organizations respond to perceived environmental pressures by

making structural changes. The scale of structural change is high since all the elements of

organizational architecture are involved. The dimension of the gap suggests a misfit between

external conditions and organizational architecture, and modification in one or two elements may

not be sufficient to reach a new fit. In fact, adaptation to environmental changes may not be

sufficient in order to provide the external fit. There is a need for providing different answers to

the challenges of the competitive context: the scope of changes radically differs from the

adaptation case.

An example of reorientation largely documented is the restructuration of Marks & Spencer:

in 1998 the retailer began a downward spiral, having failed to keep pace with competitors by

either expanding globally or developing niche markets (Beaver, 1999). The perceived gap with

its historical performance and the competitors forced the new CEO to implement a restructuring

plan. The new plan included decentralization of operations, restructuration of internal

organization (a number of top-level management changes were made), a change in human

resources policies, openness to new technologies (banking services – allow stores to accept credit

cards for the first time in its history, IT and, few years later, e-commerce) and modifications in

suppliers’ relation (cuts for the less effective parts of its UK supplier base to reduce prices).

Additionally, M&S implemented a series of new initiatives: it began to advertise more

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aggressively and to introduce more aggressive promotions and it decided to modify its value

proposition, by offering better value for money and improved service, and by better display and

presentation of merchandise (Davies, 1999; Grundy, 2005; Jackson & Sparks, 2005; Merriden,

2000; Rippin, 2005). Every element of the architecture has been modified in the turnaround.

Coherently with the reasoning, we propose the following hypothesis:

Hypothesis 3: organizations that experience major performance gap are likely to adopt

large changes in their architecture; i.e. Reorientation

Figure 1 summarizes the reasoning conducted so far and aims at exemplify the

organizational architecture changes’ typologies that assume different characteristics according to

the extension of the performance gap. The relation between (i) dimension of organizational

architecture changes and (ii) environmental feedback is summarized in figure 2.

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Insert figures 1 and 2 about here

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4. Methods

4.1. The data

To address our research questions, we merge two waves of a large survey conducted by

Unicredit, an Italian bank group. Data refer to the three years period 2001-2003 (fist wave) and

2004-2006 (second wave). In each wave, a statistically significant sample of organizations has

been selected. Unicredit realized a mixed type sample selection by disposing a sample survey for

organizations from 11 to 500 employees and a census survey for organizations with more then

500 employees. The sample is representative of Italian manufacturing organizations. The

samples have 80 layers made by 5 size classes, 4 macro areas, and 4 sectors. The response rate is

the fist wave was 28.5 %, while in the second wave was 25%. After deleting observations for

which we have missing values in one or more variables, we obtain a sample of more then 800

organizations.

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4.2. The research strategy

Our empirical strategy follows two steps. First, in an effort to measure a multidimensional

concept, we conceptualize organizational architecture using a principal component analysis

(PCA). The PCA enables us to find a proxy of the elements that define organizational

architecture. Second, in order to understand the effect of performance feedback on different

degree of organizational architecture changes, we conduct a logit and a nested logit regression

analyses.

4.3. Operationalization of the dependent variable.

To identify the key elements that compose the organizational architecture, we follow

Gulati and Puranam (2009) and Makadok (2002) and select formal architectural elements that are

unique, imperfectly imitable, and that aim to improve the productivity of the organization.

Accordingly, we choose those elements that offer a comprehensive approach to organization

characteristics including information, knowledge and hierarchical structure. Based on this

reasoning, we articulate organizational architecture in four dimensions: (1) human capital

element of organizational architecture; (2) international element of organizational architecture;

(3) ICT element of organizational architecture; (4) hierarchical element of organizational

architecture.

The human capital element of organizational architecture captures the presence of qualified

workers and their involvement in knowledge intensive and R&D activities. Organizations’

investments in knowledge intensive and R&D activities are appreciated for the potential in

augmenting the existing stock of internal knowledge (Cohen & Levinthal, 1990; Masciarelli,

2011). Moreover, employees’ skills and capabilities contribute to define the core capabilities of

the organization, playing a crucial role for the organizations’ competitiveness (Barney, 1991).

The international element of organizational architecture represents the international

involvement in international markets. Ghoshal (1987) highlights that when organizations

internationalize, they must take on completely new knowledge, including experiential knowledge

of specific foreign business practices, institutional norms and general experiential knowledge of

how to organize for foreign competition (Eriksson, Johanson, Majkgard, & Sharma, 1997).

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The ICT element of organizational architecture refers to the presence of dissemination

tools to facilitate information and knowledge flows within the organization. ICT facilitates

knowledge sharing leveling temporal and spatial barriers, creating information bases storing data

and promoting virtual knowledge teams (Kristof, Brown, Sims, & Smith, 1995). The knowledge

embedded in ICT systems, results from years of accumulating, codifying and structuring the tacit

knowledge in peoples' heads (Leonard-Barton, 1992). The most prominent instrument for

facilitating knowledge sharing and communication within the company is intranet. However, the

role of ICT in supporting knowledge diffusion within organizations goes beyond the facilities of

intranet: ICT improves communication facilitating interaction between employees and reducing

isolation. It enhances organizations’ efficiency reducing cost related to time of interaction and

increasing effectiveness of communications (Love, Irani, Ghoneim, & Themistocleous, 2006).

The hierarchical element of organizational architecture pertains to the distribution of

decision power within the organization. Simon (1969) claims that hierarchy is a mechanism for

coordinating a complex system comprising multiple specialized units. Since organizations are

viewed as institutions for integrating knowledge, hierarchical coordination involves decisions

about the mechanisms through which knowledge is diffused within the organization: therefore

hierarchies are crucial in shaping knowledge dissemination within organization boundaries

(Grant, 1996). In defining their hierarchies, organizations focus on solving the trade-off between

two opposite decisions: centralized decision-making versus delegation. Delegation has two

opposite effects: while, on the one hand, it guarantees a better use of information throughout

lower levels of the hierarchy, on the other hand, it could cause a loss of control for the higher-

level managers (Jensen & Meckling, 1976).

The multidimensional nature of organizational architecture imposes a multiple component

analysis. Specifically, we use 18 items (9 each year) of the Unicredit questionnaire. The chosen

items are: concentration of power, group control, percentage of employees involved in R&D

activities, percentage of employees with a degree, percentage of export revenues, countries

export, ICT, ICT intensity and ICT tools. Concentration of power held by managers is the

Herfindahl-Hirschman index of the stock shares owned by the three most important shareholders.

Group control is a discrete variable assuming the value of 0 if the organization is not part of a

group and the values of 1, 2 or 3 according to the position of the organization within the group

distinguishing between: (i) leading; (ii) partially owned; (iii) fully owned. This item measures the

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autonomy of the organization management in taking strategic decision. The percentage of

employees involved in R&D activities is the share of employees working in the R&D function or

with R&D mansions over the total number of employees. The percentage of employees with a

degree is the share of employees holding a university degree over the total number of employees

and it is used to compute the percentage of high skilled people working in the organization. The

percentage of export revenues over the overall revenues and countries export, measured as the

number of countries where the organization exports its products/services, represent two variables

that are aimed to capture different dimensions of the international architecture, the quantitative

(revenues) and the qualitative (number of countries). The last set of variables capture the ICT

architecture: ICT is a dummy variables indicating whether the organization has invested in ICT;

ICT intensity measures the percentage of investment in ICT over the overall investments in

machineries and industrial equipment and ICT tools is a proxy for the diversity in the typologies

of ICT used and it is constructed calculating the Herfindahl-Hirschman index of the investment

made in hardware, software and telecommunications infrastructure.

We performed two separated PCAs, one for each wave, on the selected items with a

varimax orthogonal rotation using the GPF algorithm (see Tables 1 and 2). We used the vgpf

option in Stata; this option supports the retention of the four factors we identified.

----------------------------------------

Insert Tables 1 and 2 about here

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The PCA enables us to identify the principal components that compose the organizational

architecture. The elements were formed aggregating the items tapping into each construct,

weighted by their respective factor scores. We conduct several tests to assess the psychometric

properties of the measures. Factor loadings exceed the recommended cutoff value of .60, except

for one item that has a lower value. From this analysis, we are able to identify the four

dimensions that we define architectural elements: hierarchical architecture (concentration of

power; group control), human capital architecture (percentage of employees involved in R&D

activities; percentage of employees with a degree), international architecture (percentage of

export revenues; countries export) and ICT architecture (ICT, ICT intensity and ICT tools). The

four elements of the organizational architecture are aggregated to construct the dependent

! 14!

variables of the model.

Architectural change is a measure of organizational architecture change over time. We

obtain this measure looking at the changes of each organizational architecture elements from the

period 2001-2003 to the period 2003-2006. Architectural change assumes value 0 if the

organization has not made any significant change of its organizational architecture; it assumes

value 1 if the organization presents a significant changes in 1 or 2 architectural elements -we are

in the case of organizational architecture adjustment-; it takes value 2 when the organization

presents changes in 3 or 4 architectural elements- this is the case of organizational architecture

reorientation. We have a significant change when the difference between an organizational

architecture element in the period 2001-2003 and the same element in the period 2003-2006 is

higher then one standard deviation distance from the mean.

4.4. Operationalization of independent and control variables

Our independent variables are proxies for the performance gap. The organization compares

its performance with the average industry-level performance; the difference between

organization performance, measured as the organization total sale in 2003, and the average level

of performance obtained by organizations belonging to the same sector defines the social

aspiration level. Additionally, the organization compares its current performance with its

previous performance; the difference between total sale in 2001 and total sale in 2003 defines the

historical aspiration level. The social and the historical aspiration level are used to build our

dependent variables, namely minor gap and major gap. Minor gap takes the value of 1 if either

historical aspiration level or social aspiration level are negative, 0 otherwise; major gap takes the

value of 1 if both historical aspiration level and social aspiration level are negative, 0 otherwise.

We control for organization size, calculated as the total sale that the organization has

obtained in 2003, as well as for organization age, measured as the number of years. Furthermore,

we control for R&D intensity, which is given by R&D expenditure over the total sales in 2003.

We include a dummy variable, customer satisfaction assuming value 1 if the organizations

control for degree of satisfaction of its customers, 0 otherwise. Finally, we control for R&D

intensity by industry and for organization context by mean of 4 dummy variables that identify

where the organization is located distinguishing between north-east; north-west; center and south

! 15!

of Italy.

The questions underlying the outcome variables were placed after the questions underlying

independent variables on the survey: this diminish the effects of consistency artifacts (Salancik

& Pfeffer, 1977). We performed Harman’s one-factor test on the organization-level variables

included in the models, to examine whether common method bias may augment the relationships

detected. Since we found multiple factors, and since the first factor did not account for the

majority of the variance (the first factor accounts for only 0.12 percent of the variance), potential

problems associated with common method bias were not indicated by the test (Podsakoff &

Organ, 1986).

5. Results

Table 3 reports the descriptive statistics of the variables included in the models. None of

the correlations are alarmingly high ruling out any problems regarding the possibility of

multicollinearity.

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Insert Table 3 about here

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To find empirical support for Hypothesis 1 (the presence of a performance gap increases

the likelihood that the organization will modify its organizational architecture), given the nature

of our dependent variable that takes value of 1 if the organization had changed its organizational

architecture, 0 otherwise, we used a logit model as mean of estimation. The first column in Table

4 presents the model. We support Hypothesis 1 to the extent to which the existence of a

performance gap is positive and significant in explaining the organization’s decision to change

their organizational architecture.

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Insert Table 4 about here

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Concerning Hypothesis 2 (the presence of minor performance gap increases the likelihood

that the organization will adopt small changes in their organizational architecture; i.e. adaptation)

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and Hypothesis 3 (organizations that experience major performance gap are likely to adopt large

changes in organizational architecture; i.e. reorientation), we use a nested logit estimation

technique splitting the econometric estimation into two steps since our dependent variable,

architectural change, can be considered a two stages decision. The nested logit model, first

derived by Ben-Akiva (1973), represents an extension of the multinomial logit model. However,

the multinomial logit suffers from a disadvantage known as the independence of irrelevant

alternatives (IIA). This disadvantage is caused by a property of the multinomial logit that

assumes that the relative probability of choosing between two alternatives is not affected by the

presence of additional alternatives. In our case, alternatives are not independent since, as

suggested by Hannan et al. (2003), changes in one single architectural element is likely to cause

a cascade of other changes that involve other architectural elements.

Therefore, since the IIA assumption is violated, we used a nested logit model to group

alternatives into sub-groups (nests) such that the IIA is still valid within each subgroup (Train,

2003; Winkelmann & Boes, 2006). Figure 3 describes the set-up of the specified model. The

figure shows the asymmetric nature of the data in the sense that the second level outcome only is

available if the respondent is confirmatory in the first level. Of the 755 observations available,

302 (40%) did not made any significant organizational architecture change, 423 (56%) decided

to adjustment their organizational architecture; while the remaining 30 (4%) reoriented their

organizational architecture. We follow Drucker and Puri (2005) using interaction effects to

implement such an asymmetric specification. The nested logit modeling technique also require a

reshape of the data observing each organization once for each of the three possible outcomes in

the tree depicted in figure 3. Accordingly, we use a total of 2265 observations in the analysis.

Table 4 presents the results of the nested logit regressions examining organizational architecture

changes as opposed to the organization’s decision to not change its organizational architecture.

The base category is therefore that the organization has not changed its organizational

architecture. The first column of the Table reports the result of the logit estimation. The second

column of the Table (model II) hold the results of the model in which we consider minor gap as

independent variable of organizations while column 3 (model III) depict the regression results

when studying major gap as independent variable.

Our results support Hypothesis 2 since we find that minor gap is positive and significant in

explaining the organization’s strategic decision to embrace an adaptation strategy, but it is not

! 17!

significant in explaining reorientation. Finally, we find empirical support for Hypothesis 3: our

independent variable, major gap, is positive and significant in causing major change in the

organizational architecture, leading the firms to adopt an organization’s reorientation strategy.

6. Discussions

The study has illustrated how organizations change their architectures in response to

environmental feedback. Our intent has been to investigate the link between organizational

architecture pattern of change and performance gap. Our results, described in the previous

section, support the three hypotheses we developed. More specifically, we show that

organization align their architectures to the environment following an alternative discrete model.

We find support using a logit and nested logit as means of estimation: the decision behind

adaptation or reorientation processes is influenced by the extension of the performance gap. In

fact, the presence of a gap forces firms to modify their architecture and we also proved that the

dimension of the gap influences the scale of the change. When performance feedback presents

misalignment with only one dimensions of aspirational level, organizations apply minor changes

in their architecture. On the contrary, organizations implement major changes, reorienting their

architectural, when both historical and social aspirational level presents performance gap. This

study has two relevant implications. First, modifications of organizational architecture can be

seen as a discrete model. Second, under some circumstances, organizational stability can be

beneficial (McCarthy et al., 2010; Tushman & Romanelli, 1985) and organizations are naturally

adverse to risks and changes (Greve, 1998; Tsoukas & Chia, 2002).

Overall, our results suggest that organizations modify their architectures when the level of

performance becomes distant from the desired level. Moreover, we prove that organizations

adopt different strategies according to the extent of the performance gap they are call to fit. We

believe that our work make several contribution, both for scholars and practitioners. This study

contributes to the research stream on organizational change, it extends recent works that

investigate the link between organizational change and performance and it enriches the current

understanding of the decomposability property of organizational architecture. As regard to the

contributions of this study for managers and practitioners, our study highlights the importance of

a correct identification of aspirational levels (both social and historical), decisions are taken since

on their bases. Moreover, we remark the presence of separate and interdependent elements with

! 18!

an organization.

6.1. Implications for theory

The paper contributes to the scholarly debate on characteristics of organizational

architecture and on decision processs behind organizational change. Firstly, this study informs

research on organizational change (e.g. Hannah & Freeman, 1984; Hannan et al., 2003; Tushman

& Romanelli, 1985). The literature asserts that organizational change is triggered, among other

things, by sustained low performance. Evoking contingency theory (e.g. Siggelkow, 2001) and

theory on aspiration (e.g. Greve, 1998), this study illuminates more clearly this phenomenon.

Whereas previous contributions recognize the importance of environmental threats to choose

between stability and change, they neither explain the direction nor the type of organizational

change. Our study illustrates both the direction and the type of organizational change. Relying on

our results, we argue that organizations undertake different strategies, namely adaptation and

reorientation, based on the dimension of the performance gap. Moreover, we suggest that

changes of organizational architecture are influenced by organization history and by the behavior

of similar organizations. Thus, organizations consider previous experience as well as the

behavior of other organizations in defining their strategy.

Second, we extend recent works that investigate the link between organizational change

and performance. Nickerson and Zenger (2002), using a simulation model, explains that the

strategic choices that organization makes to realign their organizational structure to

environmental changes, follow an alternative discrete model. We contribute to this literature

proving that organizations change their organizational architecture choosing between minor

changes - i.e. adaptation- and major changes –i.e. reorientation- : the dimension of the

performance gap is the break point where the advantages of organizational stability are lower the

losses in competitive advantages. The break point highlights a failures in reaching the

aspirational levels of performance.

Finally, this study enriches the current understanding of the decomposability property

(Simon, 1969) of organizational architecture. Our results confirm the hypothesis that, when

forced to modify their architecture, organizations rely on the possibility to decompose their

architecture in a set of elements. In case of small performance gap, organizations act upon one or

! 19!

two elements choosing an adaptation strategy: on the contrary, when the extent of the

performance gap is more important, organizations change all the architectural elements, adopting

a reorientation strategy. The decomposability property of organizational architecture constitutes

the basis to understand the dynamic evolution of organizational architecture since it enables the

achievement of a balance between the need for change - highlighted by the observed

performance gap - and the riskiness associated with it.

6.2. Implications for practitioners

Contributions of this study for managers and practitioners are twofold. Firstly, our study

proves that decisions are taken on the basis of two aspirational levels: historical and social. A

correct evaluation of the performance gap must be done considering both levels. In fact,

managers should appropriately identify the comparison group: organizations, in selecting their

competitors, may incorrectly specify them. The risk is to realize the existence of a performance

gap when the misalignment is with both levels, requiring a reorientation rather then an

adaptation, with higher riskiness involved.

Secondly, in this research we suggest that organizational architectures are characterized by

the presences of separate and interdependent elements and that such elements can be considered

in isolation as well and in their interrelations with the other elements in the system. Our findings

suggest that managers should be aware of such double interpretations that could lead them to

consider single element in isolation or as components of an integrated system. According to the

case (i.e. minor gap), one option might be to spend more attention at strategically manage each

organization architectural element, changing it accordingly to the environmental feedback. Under

different circumstances (i.e. major gap), the other option is to consider the interrelation among

the elements, engaging into a more complex experience that will alter completely the

architecture. The riskiness associated with the two options largely differs and, for this reasons,

the decision must be taken after a careful evaluation of the signals coming from the external

environment.

7. Concluding remarks

The study offers interesting avenues for future research. To investigate how changes on

! 20!

organizational architecture affects performance was not among the objectives of the present

work, but we believe that we could largely profit form such research. Future studies could

deepen our understanding of the appropriateness of reorientation and adaptation strategies in case

of major or minor performance gap. Moreover, we believe that this study unveils an interesting

area to be explored: decisional and implementation process behind adaptation and reorientation

mechanism and how organizations differently react to the different challenges that those

strategies poses. We believe that similar studies can significantly enlarge the findings of the

present work.

Our study is not without limitations. First, we suppose that in defining their gaps,

organizations compare themselves to other organizations in the same industry and the current

level of performance to the previous level. However, the process followed to select the

comparison group varies among organizations and each organization selects subjectively its

comparison group (Massini et al., 2005). An intriguing extension of this study would be the

exploration of organization-specific comparison groups. The second limit of our analysis is

related to the interplay between organizations and their environment. Environment can change

organizations, but, at the same time, organizations can, in a limited manner, change their

environment. Our point of view is, therefore, limited since we can only observe how the

environmental feedback affects organizations and we are not able to detect how organizations

modify their environment. Finally, it is important to acknowledge that organization strategy may

depend on the characteristics of the geographical area in which the company is located. In this

research, we used a sample of Italian manufacturing firms and the result may be affected by the

specificities of the Italian context.

! 21!

Tables and Figures

Figure 1: Conceptualization of organizational architecture changes

Figure 2: Organizational architecture changes and environmental feedback

Figure 3: Nesting structure of the implemented strategy

! 22!

Table 1: Matrix of Factor Loadings

Principal component analysis 2001-2003

ICT

architecture

International

architecture

Hierarchical

architecture

Human capital

architecture

Component 1 Component 2 Component 3 Component 4

Ict 03 0.6700 0.0049 0.0131 -0.0533

Ict intensity 03 0.3429 0.0109 -0.0295 0.1980

Ict tools 03 0.6575 -0.0091 -0.0041 -0.0089

Percentage of export revenues 03 -0.0112 0.7188 0.0210 -0.0735

Countries export 03 0.0109 0.6824 -0.0089 0.0813

Concentration of power 03 0.0039 0.0642 0.6834 -0.0355

Group control 03 0.0010 -0.0440 0.6995 0.0437

Percentage of employees involved in

r&d activities 03 -0.0241 0.0763 -0.1453 0.6764

Percentage of employees with a degree

03 -0.0168 -0.0746 0.1446 0.6965

Principal component analysis 2004-2006

International

architecture

Human capital

architecture

Hierarchical

architecture

ICT

architecture

Component 1 Component 2 Component 3 Component 4

Percentage of export revenues 06 0.6775 0.0395 0.0331 -0.0366

Countries export 06 0.6898 -0.0268 -0.0445 0.0125

Percentage of employees involved in

R&Dactivities 06 0.0228 0.7054 -0.0114 -0.0630

Percentage of employees with a degree

06 -0.0146 0.6975 0.0154 0.0736

Concentration of power 06 -0.0063 0.0706 0.7112 -0.0380

Group control 06 -0.0055 -0.0735 0.6905 0.0438

ICT 06 0.0494 -0.0143 0.0805 0.6372

ICT intensity 06 -0.1610 0.0422 -0.0861 0.6125

ICT tools 06 0.1897 -0.0351 -0.0040 0.4524

! 23!

Table 2: results of principal component analysis

Principal component analysis 2001-2003

Component Eigenvalue Percentage of variance explained Cumulative percent

1 2,170 0,241 0,241

2 1,6220 0,180 0,421

3 1,302 0,144 0,566

4 1,071 0,119 0,685

Principal component analysis 2004-2006

Component Eigenvalue Percentage of variance explained Cumulative percent

1 1,671 0,185 0,185

2 1,475 0,163 0,349

3 1,180 0,131 0,481

4 1,047 0,116 0,597

! 24!

Table 3: descriptive statistics and correlation matrix

Mean S.d. 1 2 3 4 5 6 7 8 9 10 11 12 13 14

1 Architectural

change 0.652 0.558

2 Performance gap 0.645 0.478 0.091

3 Adjustment *

Minor gap 0.151 0.358 0.032 0.331

4 Reorientation *

Minor gap 0.064 0.245 0.014 0.180 -0.102

5 Adjustment *

Major gap 0.151 0.358 0.032 0.331 -0.187 -0.102

6 Reorientation *

major gap 0.064 0.245 0.014 0.180 -0.102 -0.056 -0.102

7 Size 4,56 1,23 0.006 0.221 -0.035 0.217 -0.035 0.217

8 Age 31.22 21.13 -0.051 -0.057 -0.040 0.023 -0.040 0.023 0.010

9 Innovation 0.726 0.446 0.062 0.047 0.023 -0.004 0.023 -0.004 0.051 0.118

10 R&d intensity 0.009 0.024 0.147 0.023 0.009 0.002 0.009 0.002 0.027 -0.027 0.189

11 Customer

satisfaction 0.750 0.433 0.057 0.080 0.028 0.012 0.028 0.012 0.023 0.025 0.155 0.090

12 R&d intensity

by industry 0.009 0.009 0.124 -0.010 -0.006 0.002 -0.006 0.002 0.004 -0.087 0.149 0.389 0.084

13 North East 0.322 0.467 0.018 0.087 0.025 0.022 0.025 0.022 0.071 -0.073 0.017 0.011 0.008 0.078

14 Center 0.186 0.389 -0.092 -0.019 0.001 -0.015 0.001 -0.015 -0.046 -0.050 -0.061 -0.030 -0.090 -0.073 -0.330

15 South 0.120 0.326 0.032 -0.016 -0.020 0.020 -0.020 0.020 0.034 -0.114 -0.037 -0.059 -0.003 -0.083 -0.251 -0.171

! 25!

Table 4: Econometric models

Model I Model II Model III Logit model Nested logit model Nested logit model

Coef. S.e. Coef. S.e. Coef. S.e.

Stage2 Variables affecting the choice of "adjustment" or "reorientation"

Adjustment * minor gap 0.289 * 0.155 Reorientation *minor gap 0.341 0.349 Adjustment * major gap (-0.046) (0.241) Reorientation * major gap (0.751) * (0.400)

Stage 1 Variables affecting the choice of "ongoing change" or "significant change"

Performance gap 0.333 * (0.160) Size 0.000 (0.000) 0.000 (0.000) 0.000 (0.000) Age -0.003 (0.004) -0.003 (0.004) -0.003 (0.004) Innovation 0.089 (0.173) 0.081 (0.173) 0.098 (0.172) R&D intensity 7.176 † (5.016)) 7.131 † (5.020) 7.091 † (5.018)) Customer satisfaction 0.186 (0.175) 0.192 (0.175) 0.208 (0.175)) R&D intensity by industry 0.173 * (0.102) 0.176 * (0.100) 0.178 * (0.101) North-east -0.026 (0.185) -0.018 (0.185) -0.008 (0.184) Center -0.342 † (0.215) -0.340 † (0.215) -0.339 † (0.214) South 0.148 (0.262) 0.159 (0.262) 0.135 (0.261) North-west Benchmark Benchmark Benchmark Stage1 Constant -0.039 (0.267) 0.068 (0.258) 0.079 (0.248) Stage2 Constant - - - - N 755 2.265 2.265 LL -497.4 -610.7 -610.6 Chi2 22.98 ** 20.06 ** 23.1 **

Note: one-tailed tests: † p < .10; * p < .05; ** p < .01; *** p < .001. Standard errors in parenthesis.

! 26!

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