Organizing Alliance Portfolio Management
Dries Faems
University of Groningen
d.l.m.faems@utwente.nl
Inge Neyens
Katholieke Universiteit Leuven
Inge.neyens@econ.kuleuven.be
Paper presented at the EMNet 2011
December 1 – 3, 2011, Limassol, Cyprus
(http://emnet.univie.ac.at/)
ABSTRACT
As firms engage in an increasing number of alliances, they face the challenge of managing such
an alliance portfolio. Whereas existing studies on alliance portfolio management (APM) mainly
focus on (i) alliance experience and (ii) APM best practices, they remain silent on how firms
organize their APM. Based on survey data of 161 companies that engaged in technology
alliances between 2006 and 2008, we identify four first-order (APM formalization, APM
hierarchy, APM specialization and APM participation) and two second-order (mechanistic APM
and organic APM) dimensions that explain how firms organize the management of their
technology alliance portfolios. In addition, through testing the performance implications of these
APM dimensions, we provide evidence that organizing alliance portfolio management is an
important aspect of the alliance capability building process.
Keywords: alliances, alliance capability, alliance portfolio management, technology alliances
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INTRODUCTION
In the alliance literature, the research focus has been shifting from governing individual alliances
to managing alliance portfolios, i.e. goal-oriented management of all the alliances of a focal firm
(Hoffmann, 2005: 121; 2007: 827). Most APM studies describe how firms rely on previous
alliance experience and APM best practices to build an alliance capability. Yet, recent research
provides first indications that alliance success does not only depend on accumulated alliance
experiences and the use of APM best practices. Kale and Singh (2009), for instance, describe
how Philips has launched a Corporate Alliance Office in order to build an alliance capability. In
this description, they make clear that turning this best practice into success required strategic
decision making on how to organize this corporate alliance office and how to embed this office in
the broader organization. In a similar vein, Sarkar, Aulakh and Madhok (2009) conclude that
building alliance portfolio capabilities involves paying attention to the effective management of
different organizational processes (i.e. proactive formation, relational governance, coordination
processes). Despite these first indications, a systematic analysis of how firms organize their APM
and how this relates to alliance capability building is missing though (Wassmer, 2010).
In this paper, we want to address this research gap, exploring the organization of alliance
portfolio management and its link with alliance capability building. In order to do so, we first
empirically identify four APM dimensions (i.e. formalization, hierarchy, participation and
specialization) that are theoretically grounded in organization design theory (e.g. Aiken and
Hage, 1966; Damanpour, 1991; Galbraith, 1973) and that give an encompassing view on how
firms can make different choices regarding the organization of APM. Subsequently, we test to
what extent APM organization influences the success of a firm’s technology alliances. To
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conduct these analyses, we rely on a survey, comprising data from 161 technology intensive
companies.
This paper provides new insights on alliance portfolio management, pointing to the
organization of APM as a relevant aspect of alliance capability building. Relying on insights
from innovation portfolio literature and applying concepts from traditional organization design
literature, we show that firms need to make strategic decisions on how they want to organize their
APM in order to improve the success of the alliance portfolio. In the particular setting of
technology alliances, our data point to the advantages of an organic APM approach in which
individual alliance managers are able to participate in setting alliance-related goals and policies
and have substantial autonomy over their assigned tasks.
This paper is structured as follows. First, we review and connect existing APM and
organizational design literature to (i) identify different dimensions on how firms organize their
APM and (ii) discuss their relevance in the process of alliance capability building. Subsequently,
we describe our methodology. We then present our analyses and results. Finally, we point to the
main theoretical and managerial implications of our findings, discuss the main limitations of our
study and identify interesting avenues for future research.
ALLIANCE PORTFOLIO MANAGEMENT AND ORGANIZATIONAL DESIGN
Alliance Portfolio Management: State-of-the-Art
In his recent review paper, Wassmer (2010: p. 19) argues that existing alliance portfolio
management research mainly focuses on two distinct but interrelated topics: (i) the accumulation
of alliance experience through the engagement in multiple alliances and (ii) the use of tools and
practices to transform such alliance experience into alliance capabilities.
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Relying on a knowledge based perspective (e.g. Grant, 1996; Grant and Baden-Fuller,
2004), several scholars (Khanna, 1998; Kale et al., 2002; Draulans et al., 2003) argue that, as
firms engage in multiple alliances over time, they start building an alliance capability or ‘a firm’s
ability to identify partners, initiate alliances, and engage in ongoing management and possible
restructuring and termination of these alliances’ (Khanna, 1998: 351). Relying on alliance
experience (i.e. number of past alliances) as an indicator of the presence of alliance capabilities,
several studies provide evidence that such alliance capability has important performance
implications. Anand and Khanna (2000), for instance, provide evidence that, as firms build up
experience in managing joint ventures, they become more capable of creating value in such
alliance arrangements. In a similar vein, Hoang and Rothaermel (2005) observe that alliance
experience positively influences the ability of biotech firms to successfully complete new drug
development projects in collaboration with pharmaceutical firms. Finally, Rothaermel and Deeds
(2006) show that alliance experience positively moderates the relationship between a hightechnology venture’s R&D alliances and its new product development.
Adopting insights from organizational learning theory (Fiol and Lyles, 1985) and
evolutionary economics (Nelson and Winter, 1982), other scholars (e.g. Heimeriks and Duysters,
2007) emphasize that alliance capability building is more than just accumulating experience.
Instead, they point to the need for specific tools and practices to integrate and institutionalize the
alliance management knowledge that has been captured in previous alliances. Kale et al. (2002)
observe that firms with a dedicated alliance function (i.e. separate organizational unit charged
with the responsibility to capture prior experience) achieve greater abnormal stock market gains
following alliance announcements and report higher percentages of successful alliances than
firms that do not possess a dedicated alliance function. Draulans et al. (2003) provide evidence
that firms, which apply advanced alliance portfolio management techniques such as frequent
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cross-alliance evaluation methods and alliance training, outperform other firms in terms of
alliance success. Heimeriks, Duysters and Vanhaverbeke (2007) make an explicit distinction
between two groups of mechanisms to transform alliance experience into alliance capability. A
first group refers to a set of best practices that allows integrating the know-how, experience and
knowledge on the level of the group, unit or department that has been involved in a particular
alliance. Integrating best practices are those activities in which people share alliance related
experiences and knowledge. Examples of integrating best practices are in-house alliance training,
training in intercultural management for alliance managers, and cross-alliance evaluation. A
second group contains a set of best practices that allows institutionalizing the integrated alliance
know-how, experience and knowledge on the organizational level. Examples of such
institutionalizing mechanisms are alliance departments, knowledge management practices that
foster interaction among alliance managers from different units and a standard partner selection
approach. Heimeriks et al. (2007) show that the number of integrating practices exerts a positive
influence on alliance portfolio performance (i.e. the percentage of alliances in which the original
goals were realized), whereas institutionalizing practices do not have significant alliance portfolio
performance implications.
Organizing Alliance Portfolio Management
Relying on insights from the innovation literature, we expect that building alliance capabilities
might be more than just accumulating experience and implementing a set of best practices.
Innovation portfolio management studies (e.g. Cooper, Edgett and Kleinschmidt, 1999; Mikkola,
2001; Roussel, Saad and Erickson, 1991) have not only pointed to innovation experience and
various tools (i.e. stage gate models, bubble diagrams, strategic selection models) as accelerators
of innovation portfolio success, but also emphasized that managers have to make strategic
decisions on organizational issues such as (i) the level of formal rules and procedures with
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respect to selection and implementation of innovation projects, (ii) the level of involvement of
lower-management in innovation portfolio decisions, and (iii) the amount of innovation portfolio
specialists within the company (Damanpour, 1991). Moreover, clear indications are present that
such organizational decisions substantially impact the innovation portfolio success. Daft (1978)
already indicated that an innovation portfolio system that is characterized by high formalization
and high centralization facilitates administrative innovations but hampers technical innovations.
More recently, Jansen et al. (2006) show that firms need to implement different kinds of
organizational systems, representing different levels of centralization, formalization and
connectedness, to effectively manage explorative and exploitative innovation projects within their
portfolio.
Based on these insights, we expect that building alliance capabilities also entails effectively
organizing a firm’s alliance portfolio management system. Moreover, relying on the well
established organization design literature (e.g. Aiken and Hage, 1966; Mintzberg, 1980; Pugh et
al., 1968), we conceptualize four different dimensions of APM organization: (i) APM
formalization, (ii) APM hierarchy, (iii) APM participation and (iv) APM specialization. Below,
we define these four dimensions in detail.
APM formalization. Organization design theorists define formalization1 as (1) the presence
or absence of codified rules and procedures that may determine desired behavior in advance (e.g.
Blau and Schoenherr, 1971; Dalton et al., 1980; Galbraith, 1973; Pugh et al., 1968) and (2) the
degree of deviation which is allowed on those standards (e.g. Aiken and Hage, 1966; Damanpour,
1991; Hage and Aiken, 1967; Hall, 1963; Mintzberg, 1980; Pfeffer, 1978; Reimann, 1973).
Organizations are highly formalized in case they use many codified rules and procedures that try
to minimize deviant behavior. Relying on the definition from organizational design literature, we
define formalization of APM as the degree to which codified rules and procedures on alliance
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management are present and the degree to which these rules and procedures are used. Highly
formalized APM is characterized by many codified rules and procedures concerning alliance
management and allows no or limited deviation from these rules or procedures.
APM hierarchy. Hierarchy has been defined in organization design literature as the ‘extent
to which members are assigned tasks and then provided with the freedom to implement them
without interruption from superiors’ (Aiken and Hage, 1966; p. 498). Organizations have a strong
hierarchy if the employees experience little autonomy over the assigned tasks. Relying on this
definition, we define ‘APM hierarchy’ as the extent to which alliance managers are assigned with
alliance management tasks and then provided with the freedom to implement them without
interruption from senior management. Within an APM system with a strong hierarchy, alliance
managers seldom experience freedom to implement tasks without any interruption from senior
management whereas alliance managers operating in a system with a weak hierarchy experience
much autonomy over their assigned tasks.
APM participation. Aiken and Hage (1966, p. 498) define participation as the ‘degree to
which staff members participate in setting the goals and policies of the entire organization’. In
organizations with extensive participation, employees frequently participate in agency-wide
decisions. Relying on this definition, ‘APM participation’ can be described as the degree to
which alliance managers participate in setting the goals and policies about APM. Within an APM
system with much participation, alliance managers often participate in APM decisions; within a
system with little participation, alliance managers seldom participate in such decisions.
APM specialization. According to several organization design theorists (e.g. Galbraith,
1973; Mintzberg, 1980; Pugh et al., 1968; Reimann, 1973), the dimension of specialization refers
to the division of labor (or ‘official duties’) among a number of positions within the organization.
Specialization thus represents the different specialties found in an organization (Damanpour,
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1991). Consequently, a highly specialized organization is an organization in which a large
number of different occupational types or jobs are present. We therefore argue that a highly
specialized APM system largely consists of alliance functions that represent different specialties
whereas a less specialized APM system refers to the presence of only a small number of alliance
positions representing different specialties. For instance, a specialized APM system is
characterized by a variety of specialized positions such as relationship managers, local and
country alliance managers, gatekeepers and boundary spanners. Within a less specialized APM
system, only a few alliance positions are implemented and only few persons are responsible for
all alliance related tasks.
In sum, we argue that managers have to make strategic decisions on the level of
formalization, hierarchy, participation and specialization of their alliance portfolio management
system. Moreover, we expect that these decisions constitute an important part of the alliance
capability building process. To test this latter hypothesis, we will first empirically explore the
relevance of our four conceptual APM dimensions. Subsequently, we will test the impact of these
dimensions on alliance portfolio success. The more these APM dimensions contribute to
explaining variation in alliance portfolio success, the more important they are for explaining the
emergence of alliance capabilities.
RESEARCH METHODOLOGY
Data Collection and Sample
To empirically examine to what extent APM organization influences alliance portfolio success,
we set up an online survey study among the alliance professionals of the Association of Strategic
Alliance Professionals (ASAP). We chose for this specific population of alliance professionals
for two reasons. First, they are likely to have extensive knowledge on how their firm manages its
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alliance portfolio. Second, they are capable to understand the specific terminology and
procedures used during the online questionnaire.
Before we distributed this questionnaire, we evaluated its face validity (in terms of its
perceived relevance, length, clarity, completeness …) based on seven semi-structured interviews
with European and American alliance professionals and 21 interviewees with managers from
small or medium sized companies in the Netherlands.
We collected our data in January 2009. We used the ASAP database as it provides access to
valid email addresses of 2329 organizations. We decided to send an invitation letter to those
alliance professionals that we couldn’t contact by email. One week later, we sent a reminder to
those alliance professionals that did not yet (fully) complete the questionnaire at that moment in
time. We tried to encourage the participation of the alliance professionals in several ways. First,
we promised them an executive summary report of the final results and a presentation of the first
results at the ASAP Summit 2009 (February 2009), a conference in which alliance professionals
can share their specialized alliance experiences. Second, we put an announcement in the ASAP
newsletter and on the ASAP web page. Third, we called all non (or partial) respondents to ask for
their participation.
In total, 329 organizations participated in the study, which is a firm response rate of 14%.
Such a response rate corresponds with response rates of other worldwide survey studies,
generally ranging between 6% and 16% (Harzing, 2000). Among these 329 organizations, 161
respondents indicated that their firm engaged in technology alliances (i.e. alliances in which
technological activities are at least part of the collaborative effort, Hagedoorn and Schakenraad,
1994) between 2006 and 2008. These firms were also asked additional questions on 1) how their
firm managed and organized its technology alliances between 2006 and 2008 and on 2) the
success of their technology alliances in 2008. We chose to focus on one particular kind of
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alliance (i.e. technology alliances), because existing research (Draulans et al., 2003; Hoffmann,
2007) already indicates that other kinds of alliances (e.g. marketing alliances, co-production
alliances, supplier alliances) might require a different approach in terms of alliance portfolio
management.
Sometimes, we received answers from multiple respondents of the same organization
because this organization had different ASAP memberships. As the -technology intensive- firm is
the level of analysis in this study, we selected one respondent for each firm. Our selection of the
respondents is based on the following criteria, ranked in order of importance: First, we deleted
respondents with missing values on the core variables in this study (i.e. the APM dimensions).
Second, we compared the consistency of the answers of multiple respondents working in the
same firm with corporate information that we retrieved via a web search. We deleted those cases
with inconsistent answers. Third, we selected those respondents occupying a position which
provides a complete overview on the alliance portfolio of firms (e.g. the vice-president of
alliances or the alliance director). This selection process resulted in our final sample of 161
unique respondents.
Measurements
The four APM dimensions. We used three validated measurement scales from the
organizational design literature (Aiken and Hage, 1966; Cunningham and Rivera, 2001; Pugh,
Hickson, Hinings and Turner, 1968; Schminke, Ambrose and Cropanzo, 2000) to measure ‘APM
formalization’, ‘APM hierarchy’ and ‘APM participation’. We made some minor adjustments to
these scales to take into account the specific characteristics and context of APM. Besides, we
constructed a new scale to measure ‘APM specialization’. Table I gives an overview of the
original items used in organizational design studies and displays the adjusted or self-constructed
items we use to measure the four APM dimensions.
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------------------------------Insert Table I about here
------------------------------We measured ‘APM formalization’, ‘APM hierarchy’, and ‘APM specialization’ by asking
the respondents to indicate to what extent they agreed with several statements about how
technology alliances are managed within their company (Table I). The answer categories were
disagree (=1), rather disagree (=2), neither agree, nor agree (=3), rather agree (=4), agree (=5)
and don’t know (=6). ‘APM participation’ is measured by the frequency that technology alliance
managers participate in four decisions on APM. The answer categories were never (=1), seldom
(=2), sometimes (=3), often (=4), always (=5) and don’t know (=6).
Technology Alliance Portfolio Success. In order to examine whether the organization of
the technology alliance portfolio management contributes to alliance capability building, we
needed a measure of technology alliance portfolio success. Researchers have discussed both the
benefits and shortcomings of ‘objective’, ‘subjective’ and combined approaches to measure the
alliance portfolio success of firms (e.g. Heimeriks et al., 2007; Kale et al., 2002, Kale and Singh,
2007). In this respect, some studies (e.g. Geringer and Hebert, 1991; Kale et al., 2002)
empirically compare both measurement methods and conclude that managerial assessments
adequately measure alliance portfolio performance. In line with previous research (e.g. Heimeriks
et al., 2007), we measure technology alliance portfolio success by asking the respondents to
indicate the percentage of the company’s technology alliances that is a success. The answer
categories of this question are 0% (=1), 1-20% (=2), 21-40% (=3), 41-60% (=4), 61-80% (=5)
and 81-100% (=6). In further analyses, we merged the answer categories of 0% (=1) and 1-20%
(=2) into one category (0-20%).
Control variables. In our analyses, we first control for a firm’s alliance experience. As
stated above, several APM researchers (e.g. Anand and Khanna, 2000; Gulati, Lavie and Singh,
10
2009; Hoang and Rothaermel, 2005; Kale et al., 2002) point to the relevance of alliance
experience as a predictor of alliance portfolio success. We measure alliance experience by the
natural logarithm of 1 + the number of technology alliances in 2006.
As mentioned above, Heimeriks et al. (2007) propose a distinction between two categories of
practices to manage alliance portfolios, i.e. integrating and institutionalizing best practices. In our
questionnaire, we included exactly the same list of tools, functions and processes as used by
Heimeriks et al. (2007). The first category (i.e. integrating practices) indicates how many of the
following best practices are present within the firm: internal alliance training, alliance best
practices, training in intercultural management for alliance managers, external alliance training,
alliance metrics, culture programs and cross-alliance evaluation. The internal consistency
(Chronbach’s alfa) of this scale is 0.70. The second category (i.e. institutionalizing practices)
represents how many of the next best practices are present within the firm: alliance department,
alliance managers, vice-president of alliances or chief alliance officer, rewards and bonuses for
alliance managers are tied to alliance success, intranet, local alliance managers, alliance managers
from different units/divisions formally exchange their experience, country specific alliance
policies and a standard partner selection approach. The internal consistency (Chronbach’s alfa) of
this scale is 0.76. We subsequently transformed the scale scores of both mechanisms to an 11point scale ranging from 0 to 102.
A third characteristic we control for is the strategic importance that firms attach to their
alliances. Apart from alliances, firms might opt to 1) internally achieve their strategic objectives
or 2) achieve them via mergers or acquisitions (de Man and Duysters, 2005). Moreover, several
studies indicate that, the higher the strategic importance of alliances, the more time and resources
companies are willing to invest in them, which subsequently improves alliance portfolio success
(Goerzen, 2005; Hoffman, 2007). In our analyses, we therefore include a measurement of the
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strategic importance of alliances. We measure this variable by asking the next question: ‘How
important are alliances to realize your company strategy?’ The answer categories range from not
at all important (=1) to very important (= 5).
A fourth firm characteristic we include in our analyses is the industry in which the firm is
situated. Table VII illustrates that our sample largely consists of firms belonging to the
telecommunication and information technology industry (i.e. IT software, IT hardware) and -to a
smaller extent- to the services industry. We constructed two dummies to represent the ICT
industry (telecommunication, Information Technology) and services industry (financial services,
IT services, other services) and added a third dummy representing those firms that do not belong
to one of these two kinds of industries (i.e. chemicals, pharma/biotech, other manufacturing,
public sector and another sector).
Finally, we control for firm size. We measure firm size by a dummy representing
companies with a worldwide sales volume (in US$) below 1 billion US$ and a dummy
representing firms with a worldwide sales volume (in US$) equal or above 1 billion US$.
ANALYSES AND RESULTS
In this paragraph, we first empirically explore how firms organize their APM. Next, we present
the main descriptive statistics on APM organization. Finally, we analyze the impact of APM on
technology alliance portfolio success.
How Do Firms Organize their APM?
1st Order Factor Analysis. To explore the different APM dimensions, we first conducted an
explorative factor analysis, using Principal Axis Factoring with a Promax rotation (Table II)3.
This analysis clearly points to a four factor solution as the eigenvalue of the fifth factor decreases
below the standard of 1 and the scree plot shows a significant drop of the eigenvalue from a four
factor solution to a fifth factor solution. The four factors explain together 61% of the variance of
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the items. Except for one item measuring APM specialization (i.e. ‘In our company, there is a
wide variety of experts to whom technology alliance managers can ask for support’), all APM
items had factor loadings above 0.60 on their respective APM dimensions.
--------------------------------Insert Table II about here
--------------------------------Subsequently, we performed a confirmatory analysis to optimize the original factor
structure. The modification indices of the confirmatory factor analysis indicated that a better
model fit (χ²[71]= 113.46; CFI= .96; RMSEA= .06; SRMR= .06) could be achieved by several
changes. In particular, this new model omitted two items of the scale APM hierarchy and one
item of the scales APM formalization and APM participation (Table III). Consequently, APM
formalization and APM specialization are measured by four items, whereas APM participation
and APM hierarchy are measured by three items.
---------------------------------Insert Table III about here
---------------------------------We computed the Chronbach’s alfa to examine the internal consistency of the four final
APM scales and found all four scales to be sufficiently reliable with their Chronbach’s alfa
exceeding 0.70. The results of the confirmatory factor analysis further allowed us to calculate the
factor scores of the four APM dimensions.
2nd Order Factor Analyses. Apart from distinguishing several dimensions, organizational
design theorists (Child, 1972; Grinyer et al., 1980; Hinings and Lee, 1971; Payne and Mansfield,
1973; Pugh et al., 1968) also acknowledge the mutual dependencies or correlations between these
dimensions. In line with these scholars, we provide an overview of the correlations of the four
factors in Table IV. The table displays overall positive correlations between APM formalization,
APM specialization and APM participation and negative correlations between (i) APM hierarchy
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and (ii) APM formalization and APM participation. APM hierarchy does not significantly
correlate with APM specialization.
--------------------------------Insert Table IV about here
--------------------------------Given the correlations between the factor scores, we performed a second explorative factor
analysis to explore the underlying second-order factor structure. We chose for a Principal
Component Analysis with a Varimax Rotation in order to obtain a clear interpretable, orthogonal
second-order factor structure. This analysis points to a two factor solution as the eigenvalue of
the third factor decreases below the standard of 1. The two factors explain together 78.11% of the
variance of the four dimensions. The first factor strongly correlates with APM hierarchy and with
APM participation. The loading on APM hierarchy has a negative sign, whereas the loading on
APM participation has a positive sign. We therefore label this factor as ‘organic APM
organization' (Burns and Stalker, 1961). The second factor strongly correlates with APM
specialization and APM formalization. We label this factor as 'mechanistic APM organization'
(Burns and Stalker, 1961) (see Table V).
------------------------------Insert Table V about here
------------------------------Descriptive statistics. Table VI gives an overview of the descriptive statistics and the
correlations between alliance experience, the two categories of APM best practices, the strategic
importance firms attach to alliances and the two ways of organizing APM.
--------------------------------Insert Table VI about here
--------------------------------Table VII shows the results from additional ANOVA’s and displays the relationships
between (i) two company characteristics (i.e. the industry and sales volume) and (ii) other control
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variables (alliance experience, the APM learning mechanisms and the strategic importance of
alliances) and APM organization.
---------------------------------Insert Table VII about here
---------------------------------Impact of APM on the Success of the Technology Alliance Portfolio
Ordinal Regression Analyses. To examine the impact of APM organization on technology
alliance portfolio success, we performed ordinal regression analyses.
---------------------------------Insert Table VIII about here
---------------------------------Model 1 (Table VIII) includes all control variables. This model shows that alliance
experience does not exert a significant influence on success, whereas the strategic importance
firms attach to their alliances strongly and positively impacts alliance portfolio success (B=.70;
p<.01). In line with Heimeriks et al. (2007), we observe that integrating practices are positively
associated with alliance success. In contrast to Heimeriks et al. (2007), who do report a nonsignificant relationship between the number of institutionalizing practices and alliance success,
our results show that institutionalizing practices diminish the percentage of a firm’s successful
technology alliances. This latter result might suggest that, in the particular setting of technology
alliances, the use of institutionalizing learning mechanisms is more disadvantageous than in other
alliance settings.
In Model 2, we include the variables representing APM organization. The total explained
variance in Model 2 is 33%. This model shows no significant relationship between mechanistic
APM and technology alliance portfolio success. At the same time, we observe that an organic
way of APM organizing is positively associated with the success of technology alliances (B=
0.53, p<.05). This result is in line with the findings of Hoffmann (2005) who emphasizes the
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advantages of maximizing alliance managers’ responsibility for the management of their alliance
and the arguments of Draulans et al. (2003), who point to the advantages of positioning alliance
portfolio management responsibilities at lower levels in the organization.
We also observe that adding these APM organization variables significantly improves the
explanatory value of our model (R²change = 6%). Therefore, we conclude that technology
alliance portfolio success is significantly influenced by strategic decision making on how to
organize APM. More specifically, our results suggest that, in the setting of technology alliances,
building an alliance capability requires not only the implementation of integrating best practices,
but also asks for an organic approach towards organizing alliance portfolio management.
Additional analyses. We also tested for the existence of inversed U-shaped relationships
between the APM organization dimensions and technology alliance portfolio success. In addition,
we tested for the existence of interaction effects between alliance experience, the learning
mechanisms and the APM organization. However, no additional significant results were found in
these analyses.
DISCUSSION AND CONCLUSION
In this final section, we first discuss the main implications of our findings. Subsequently, we
point to the main limitations of our study and identify interesting avenues for future research.
Organizing APM as Essential Part of Alliance Capability Building
Relying on insights from the knowledge based perspective, organizational learning theory and
evolutionary economics, previous studies have focused on how firms (1) accumulate alliance
experience and (2) transform this alliance experience via APM best practices in order to build
their alliance capabilities. In line with recent studies (Heimeriks et al., 2007; Kale et al., 2002;
Kale and Singh, 2007), we find that the presence of specific APM best practices has a substantial
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effect on technology alliance portfolio success. In this way, our findings seem to confirm that
alliance capability building differs from just accumulating experience.
At the same time, we relied on insights from innovation portfolio literature and concepts
from organization design theory to identify an additional aspect of alliance portfolio
management. In particular, we emphasized the relevance and importance of organizing the
alliance portfolio management system and identified multiple underlying dimensions. Moreover,
we were able to empirically demonstrate that how firms organize their alliance portfolio
management substantially influences alliance portfolio success. In this way, we can conclude that
effectively organizing APM is an essential part of the alliance capability building process within
firms.
Effectively Managing Technology Alliance Portfolios
Technology alliances have been recognized as an important mechanism to supplement and
complement a firm’s internal innovation efforts (Faems et al., 2005; Hagedoorn, 2002;
Lichtenthaler and Lichtenthaler, 2009). Although most studies have emphasized the benefits of
technology alliances in terms of stimulating innovation performance, several studies provide
indications that there are limitations to the positive impact of technology alliances. Examining the
impact of technology alliance portfolio diversity (i.e. the number of different partners in a
technology alliance portfolio) on financial performance, Faems et al. (2010), for instance,
observed that, in the short term, the cost-increasing effects of expanding technology alliance
portfolios are higher than the its value-enhancing effects. Other scholars (Deeds and Hill, 1996;
Rothaermel and Deeds, 2006) found an inversely U-shaped relationship between the number of
technology alliances and innovation performance, suggesting that firms face limitations regarding
how many technology alliances they can absorb. Based on these findings, these scholars
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emphasized the need for research into how technology alliance portfolios can be effectively
managed.
Based on our findings, we can provide specific guidelines on how to effectively manage
technology alliance portfolios. First, we emphasize that having a rich history of prior technology
alliances is not a sufficient condition to guarantee success in future technology alliances. Instead,
our data suggest that firms have to actively invest in APM practices and make strategic decisions
on how to organize APM in order to achieve technology alliance portfolio success. In particular,
we emphasize that managers should invest in tools and practices that stimulate integration of
technology alliance knowledge within single groups, business units or departments instead of
institutionalization technology alliance knowledge across groups, business units and departments.
At the same time, we stress the benefits of an organic APM system in which alliance managers
participate in defining alliance management policies and procedure and receive substantial
autonomy in their day-to-day activities.
Limitations and Future Research
A first limitation is related to our particular focus on technology alliances. This specific focus
hampers the generalization of our findings to other, broader defined alliance portfolios (e.g.
alliance portfolios that include marketing alliances as well). Moreover, this different empirical
setting might explain why our results differ from findings of previous studies. For instance, we
find that institutionalizing learning mechanisms negatively influence technology alliance
portfolio success. This finding might be particularly true in the context of technology alliances,
but cannot be generalized to the context of broader defined alliance portfolios.
Second, the descriptive statistics show that firms organize APM in different ways. The
results of our ANOVA analyses (see Table VII) show no significant relationship between firm
18
characteristics (i.e. size and industry) and APM organization. We therefore encourage future
research that explores the antecedents of APM organization.
Recent research (Schreiner, Kale and Corsten, 2009; Wassmer, 2010) has started making an
explicit distinction between alliance capabilities (i.e. the ability to successfully manage individual
alliances) and alliance portfolio capabilities (i.e. the ability to maximize synergies and minimize
conflicts across alliances). Although our survey allowed measuring the degree of technology
alliances that is a success, we did not have indicators of the extent to which firms manage to
maximize synergies and minimize conflicts among different technology alliances. Future research
that looks at the impact of different alliance portfolio management aspects (i.e. experience, tools
and practices, organizational dimensions) on alliance portfolio capability building therefore
seems very relevant.
Finally, whereas we focused on the management of alliance portfolios, other scholars (e.g.
Duysters and Lokshin, 2010; Jiang, Tao and Santoro, 2010; Luo and Deng, 2009) have recently
examined the performance implications of the size and diversity of alliance portfolios. Future
studies on the interaction between these managerial and configurational aspects might be very
relevant.
Despite these limitations, we believe that this paper substantially contributes to a more finegrained understanding of how firms organize their alliance portfolio management. We hope that
our findings might help managers in optimizing their alliance portfolio activities and might
stimulate other scholars to further examine alliance portfolio management and its performance
implications.
19
NOTES
1
As scholars from organization design literature do not consistently distinguish between formalization and
standardization (Damanpour, 1991), we refer to both dimensions by using the concept of ‘formalization’.
2
If a respondent partially completed the questions about integrating and institutionalizing learning mechanisms, we
extrapolated a general scale score based on the completed items.
3
Because of a substantial amount of missing values on the APM items (ranging from 6% to 16%), we decided to
perform a missing value analysis based on Estimation Maximization (EM) imputation. This particular imputation
strategy calculates missing values via EM algorithms. In this EM analysis, we included all APM items that are used
to measure the four first-order factors. The Little MCAR test shows that the data is missing completely at random
(χ²[356]= 318.43, p=.924) and thus meets the criterion for EM imputation (Little and Rubin,1987; Roth, 1994).
20
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TABLE I
The Items Measuring the Four APM Dimensions
APM
dimension
(references)
Formalization
(Cunningham
and Rivera,
2001; Pugh,
Hickson,
Hinings and
Turner, 1968;
Schminke,
Ambrose and
Cropanzo,
2000)
Hierarchy
(Aiken and
Hage, 1966;
Schminke,
Ambrose and
Cropanzo,
2000)
Participation
(Aiken and
Hage, 1966;
Schminke,
Ambrose and
Cropanzo,
2000).
Specialization
(self
constructed)
Original items
Translated items
The department has a large number of
written rules and policies.
A “rules and procedures” manual exists
and is readily available within the
company.
There is a formal orientation program for
most new members of the department.
There is a complete written job
description for most jobs in this
department.
The organization keeps a written record
of nearly everyone’s job performance.
I have to ask my boss before I do almost
anything.
The company has a large number of written rules and
policies about technology alliance management.
A “rules and procedures” manual on technology alliance
management exists and is readily available within the
company.
There is an alliance life cycle plan that prescribes the
various steps of forming a technology alliance.
The responsibilities of the employees involved in
technology alliances are written down.
The organization keeps a written record of nearly every
technology alliance and its performance.
For almost anything concerning technology alliance
management, senior management has to be consulted
first.
Even small matters have to be referred
Even small matters regarding technology alliance
to someone higher up for a final answer.
management have to be referred to someone higher up
for a final answer.
Any decision I make has to have my
Any decision regarding technology alliances needs
boss' approval.
senior management approval.
There can be little action taken here until Little action regarding technology alliances can be taken
a supervisor approves a decision.
until ‘someone higher up’ (e.g. vice president of alliances,
chief executive officer) approves a decision.
A person who wants to make his own
In our company, technology alliance managers who want
decisions would be quickly discouraged
to make their own decisions would be quickly
here.
discouraged.
How frequently do you participate in
How frequently did technology alliance managers
decisions on the adoption of new
participate in the decisions to adopt new policies about
policies?
technology alliance management?
How frequently do you participate in the
How frequently did technology alliance managers
decisions on the adoption of new
participate in the decisions to adopt a new approach
programs?
about technology alliance management?
How frequently do you usually participate How frequently did technology alliance managers
in the decision to hire new staff?
participate in the decisions to select team members for
the technology alliances they manage?
How frequently do you usually participate How frequently did technology alliance managers
in decisions on the promotion of any of
participate in the decisions to start new technology
the professional staff?
alliances?
In our company, a wide variety of people is present that are specialized in a particular aspect of
technology alliance management.
In our company, there are many kinds of specialists responsible for the management of technology
alliances.
In our company, there are many different positions to support the management of technology
alliances.
Tasks related to technology alliance management are divided across many different specialists.
In our company, there is a wide variety of experts to whom technology alliance managers can ask for
support.
27
TABLE II
The APM Dimensions: An Explorative, First-Order Factor Analysis
F1
F2
F3
F4
0,85
0,04
0,23
0,39
0,82
-0,11
0,32
0,32
0,78
-0,01
0,17
0,31
0,76
-0,10
0,35
0,31
0,65
-0,12
0,36
0,28
0,03
0,85
-0,19
-0,02
0,04
0,83
-0,29
0,09
-0,08
-0,14
0,75
0,67
-0,09
-0,37
-0,10
-0,18
-0,08
0,60
-0,42
-0,01
0,25
-0,37
0,94
0,19
0,34
-0,39
0,88
0,19
0,32
-0,26
0,78
0,31
0,29
-0,05
0,68
0,11
In our company, a wide variety of people is present that are specialized in a particular
aspect of technology alliance management.
In our company, there are many kinds of specialists responsible for the management
of technology alliances.
0,37
0,04
0,14
0,83
0,33
0,01
0,04
0,77
In our company, there are many different positions to support the management of
technology alliances.
Tasks related to technology alliance management are divided across many different
specialists.
In our company, there is a wide variety of experts to whom technology alliance
managers can ask for support.
0,34
-0,08
0,21
0,76
0,16
-0,09
0,24
0,62
0,37
-0,35
0,42
0,46
Survey items
APM formalization (eigenvalue= 5.18)
A "rules and procedures" manual on technology alliance management exists and is
readily available within the company.
The company has an alliance life cycle plan that prescribes the various steps of
forming a technology alliance.
The company has a large number of written rules and policies about technology
alliance management.
The responsibilities of the employees involved in technology alliances are written
down.
The company keeps a written record of nearly every technology alliance and its
performance.
APM hierarchy (eigenvalue= 3.06)
For almost anything concerning technology alliance management, senior
management has to be consulted first.
Even small matters regarding technology alliance management have to be referred to
someone higher up for a final answer.
Any decision regarding technology alliances needs senior management approval.
Little action regarding technology alliances can be taken until ‘someone higher up’
(e.g. vice president of alliances, chief executive officer) approves a decision.
In our company, technology alliance managers who want to make his/her own
decisions would be quickly discouraged.
APM participation (eigenvalue= 1.77)
How frequently did technology alliance managers participate in the decisions to adopt
new policies about technology alliance management?
How frequently did technology alliance managers participate in the decisions to adopt
a new approach about technology alliance management?
How frequently did technology alliance managers participate in the decisions to select
team members for the technology alliances they manage?
How frequently did technology alliance managers participate in the decisions to start
new technology alliances?
APM specialization-reversed (eigenvalue= 1.49)
Extraction Method: Principal Axis Factoring.
Rotation Method: Promax with Kaiser Normalization.
28
TABLE III
The APM Dimensions: A Confirmatory, First-Order Factor Analysis
Survey items
APM formalization
The company has an alliance life cycle plan that prescribes the various steps of forming a
technology alliance.
The responsibilities of the employees involved in technology alliances are written down.
The company has a large number of written rules and policies about technology alliance
management.
The company keeps a written record of nearly every technology alliance and its performance.
APM hierarchy
Even small matters regarding technology alliance management have to be referred to someone
higher up for a final answer.
In our company, technology alliance managers who want to make his/her own decisions would
be quickly discouraged.
Little action regarding technology alliances can be taken until ‘someone higher up’ (e.g. vice
president of alliances, chief executive officer) approves a decision.
APM participation
How frequently did technology alliance managers participate in the decisions to adopt new
policies about technology alliance management?
How frequently did technology alliance managers participate in the decisions to adopt a new
approach about technology alliance management?
How frequently did technology alliance managers participate in the decisions to select team
members for the technology alliances they manage?
APM specialization
In our company, a wide variety of people is present that are specialized in a particular aspect of
technology alliance management.
In our company, there are many different positions to support the management of technology
alliances.
In our company, there are many kinds of specialists responsible for the management of
technology alliances.
Tasks related to technology alliance management are divided across many different specialists.
Chi sq (df)
CFI (Bentler’s Comparative Fit Index)
TLI
RMSEA (Root Mean Square Error Of Approximation)
29
S.E.
0,83
0,79
0,70
0,69
0,74
0,72
0,67
0,96
0,88
0,79
0,86
0,75
0,75
0,59
113,46 (71)
0,96
0,95
0,06
TABLE IV
Descriptive Statistics, Correlations and Chronbach's Alfa: First-order APM factors
Min.
Max.
SD
N
1.
2.
1. APM formalization
-1.28
1.75
0,79
161
0,84
2. APM hierarchy
-1.49
1.94
0,79
161
-0,17*
0,75
3. APM participation
-2.19
1.28
0,85
161
0,38***
-0,61***
0,90
4. APM specialization
-1.43
1.19
0,67
161
0,43***
0,02
0,20*
*** Significance at the .001 level; ** Significance at the .01 level; * Significance at the .05 level.
Chronbach’s alfa on diagonal (bold and cursive)
30
3.
4.
0,83
TABLE V
Second-Order Factor Structure: Factor Loadings
Factor 1 (eigenvalue:
Factor 2
1.20)
(eigenvalue: 1.92)
APM hierarchy
-0,92
0,06
APM participation
0,85
0,29
APM specialization
-0,06
0,88
APM formalization
0,27
0,79
31
TABLE VI
Descriptive Statistics and Correlations: APM Dimensions, Learning Mechanisms and Control Variables
Min.
Max.
Mean
SD
N
1
2
3
4
5
1. Alliance experience
0
8.52
2.09
1.56
160
1
2. Integrating learning
0
10
4,78
2,94
161
0,24**
1
0
10
5,73
2,82
161
0,26**
0,44***
1
1
5
4,04
1,06
161
-0,01
0,20*
0,10
1
5. Organic APM
-3.05
2.00
0,00
1,00
161
0,09
0,24**
0,27**
0,19*
1
6. Mechanistic APM
-2.51
2.64
0,00
1,00
161
0,28***
0,40***
0,46***
0,05
0,00
mechanisms
3. Institutionalizing
learning mechanisms
4. Strategic importance of
alliances
*** Significance at the .001 level; ** Significance at the .01 level; * Significance at the .05 level.
32
TABLE VII
ANOVA: APM and Control Variables
Mean (Industry)
F
Mean (Sales volume)
F
ICT
Services
Other
sales volume
sales volume
(N= 67;
(N= 26;
(N= 67;
< 1 billion US$
≥ 1 billion US$
41.9%)
16.3%)
41.9%)
(N= 76; 47,5%)
(N= 84; 52,5%)
1. Alliance experience
2.11
1.72
2.28
1.40
1.33
2.78
43.35***
2. Integrating learning
4,18
5,31
5,13
2,34
4,15
5,31
0,22*
5,90
6,66
5,13
3,14*
4,90
6,43
6,21***
4,07
3,77
4,16
1,37
4,16
3,98
1,22
5. Organic APM
0,07
0,19
-0,14
1,29
0,04
-0,04
6,47
6. Mechanistic APM
-0,04
0,23
-0,05
0,85
-0,20
0,19
12,69
mechanisms
3. Institutionalizing learning
mechanisms
4. Strategic importance of
alliances
*** Significance at the .001 level; ** Significance at the .01 level; * Significance at the .05 level. †Significance at the .10 level.
33
TABLE VIII
Regression Analyses: Learning Mechanisms and APM Organization Predicting Success of Technology Alliances
Model 1
Model 2
Technology alliance portfolio success: 0-20%
3,22** (1,11)
3,00* (1,20)
Technology alliance portfolio success: 21-40%
3,93** (1,13)
3,73** (1,22)
Technology alliance portfolio success: 41-60%
4,94*** (1,17)
4,84*** (1,26)
Technology alliance portfolio success: 61-80%
6,26*** (1,22)
6,25*** (1,31)
Organic APM
/
0,53* (0,21)
Mechanistic APM
/
-0,28 (0,24)
Technology alliance portfolio success: 81-100%
(Threshold)
Explanatory variables (Location)
Control variables
Alliance experience
0,21 (0,16)
0,21 (0,16)
Integrating learning mechanisms
0,13† (0,08)
0,14† (0,08)
Institutionalizing learning mechanisms
-0,17* (0,08)
-0,19* (0,08)
Strategic importance of alliances
0,70** (0,20)
0,68** (0,21)
Industry: ICT (reversed)
0,35 (0,42)
0,38 (0,42)
Industry: services (reversed)
0,95†
(0,56)
1,10† (0,57)
Sales volume
-0,17 (0,45)
-0,13 (0,46)
df
7
9
N
103
103
284,81
276.17
30,44***
39,08***
0,27
0,33
-2Log Likelihood
χ²
Nagelkerke R²
†
*** Significance at the .001 level; ** Significance at the .01 level; * Significance at the .05 level. Significance at the .10 level.
34