“A Comparison of Organizational FactorsInfluencing New Product Success

in Internal and Alliance Based Products”

Eugene SivadasF. Robert DwyerEmerson College

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A Comparison of Organizational Factors InfluencingNew Product Success in Internal and

Alliance Based Processes

Eugene Sivadas

F. Robert Dwyer

Address Correspondence to:

c

Eugene SivadasAssistant ProfessorSchool of Communication, Management, and Public PolicyEmerson College100 Beacon StreetBoston, MA 02116Phone: (617) 8248857; Fax: (617) 824-8749; Email: Esivadas@emerson.edu

Eugene Sivadas is an Assistant Professor of Integrated Marketing Communications, Emerson College,Boston, MA and F. Robert Dwyer is the Joseph S. Stem Professor of Marketing, Department of Marketing,University of Cincinnati, Cincinnati, OH. The research support of the Institute for the Study of BusinessMarkets and the Direct Marketing Policy Center is gratefully acknowledged. The authors thank KarenMachleit, Ann Welsh, and B.J. Zirger for their comments on earlier drafts of this paper.

A Comparison of Organizational Factors InfluencingNew Product Success in Internal and

Alliance Based Processes

ABSTRACT

New products provide increased sales, profits, and competitive strength for most organizations. However,nearly 50 percent of the new products that are introduced each year fail. Organizations thus find themselvesin a double bind. On the one hand they have to consistently innovate to remain competitive, but on the otherhand innovation is risky and expensive. Many organizations are forming business alliances to quicken thepace of and reduce risks associated with innovation. Yet, by some estimates, 70 percent of these alliancesfail. Many of the prescriptions for successful alliance management clash with recommendations foreffective innovation management. Using the Zirger-Maidique model, this paper develops testablehypotheses by integrating the new products and alliance literature. Internal new product development

2 : (NPD) efforts are compared and contrasted with new product development efforts conducted underalliances. The model is tested with data from a sample survey in the semiconductor manufacturing contextand replicated in the healthcare sector. Results suggest that cooperative competency, clarity of agreement,fit, and clan-oriented administrative mechanisms contribute to new product success. The importance ofvarious factors in the model on internal and external NPD is discussed.

INTRODUCTION

New products provide increased sales, profits, and competitive strength for most organizations.

Many successful corporations such as JVC (which pioneered the VHS format for home VCRs) and Apple

Computer owe their fortunes to new products they developed (Cooper 1993). A study of more than 700

Fortune 1000 companies indicated that new products would provide about a third of their profits over the

next five years (Booz, Allen, and Hamilton 1982).

On the other hand, nearly 50 percent of the new products that are introduced in the market place

each year fail, causing considerable financial loss and embarrassment to their promoters (Business Week

1993; Zirger and Maidique 1990). At the extreme, Ford Motor Co. lost $250 million with the Edsel in 1958

and RCA’s failed VideoDisc player launched in 1981 cost them $500 million (Salmans 1984).

Thus, many organizations are entering business alliances to offset many of the pitfalls associated

with the innovation process. A business alliance is “an ongoing, formal, business relationship between two

or more independent organizations to achieve common goals” (Sheth and Paxvatiyar 1992, p. 72).

Organizations enter alliances to quicken the pace of innovation, overcome budgetary constraints, spread out

risks, and gain access to resources (e.g., technological, financial) not otherwise available to them (Bleeke

and Ernst 1993, Varadarajan and Cunningham 1995). For example, Intel has entered into an alliance with

Hewlett-Packard to develop a single

computers (Wall Street Journal 1994).

Nevertheless, many alliances

Some estimates put the failure rate of

computer chip capable of running software in both PCs and large

tend to be unstable and a large number of these fail (Gates 1993).

alliances as high as 70 percent (Business Week 1986; Parkhe 1993).

The potential for conflict and a clash of interest among alliance partners is inherent. Either party can

opportunistically use the alliance to learn the other’s business or technological secrets (Bucklin and

Sengupta 1993). Furthermore, because alliances are largely self-governing; there are no practical higher

authorities who cti ensure that errant partners will be brought in line (Parkhe 1993).

1

There is some speculation that administrative mechanisms that serve well to manage these

uncertainties in alliance impair the new product development objectives. Indeed, Bidault and Cummings

( 1994) suggest that there is a fundamental clash between the “logic of innovation” and the “logic of

alliances. ” Alliances succeed when goals and responsibilities of partners are clearly detailed (Hausler,

Hohn, and Lutz 1994; Lorange and Roos 1992). Innovation, however, requires a measure of flexibility to be

granted to those directly involved with the project. Alliance partners seek joint control of a project and

departures from prior agreements may involve renegotiation, and, thus may impede the flexibility required

for effective innovation. Organizations enter into alliances to take advantage of partners’ knowledge and

strength but most alliances are characterized by lack of trust (Lorange and Roos 1992). This restricts the

free flow of information, critical for new product success (e.g., Barclay 1992a, 1992b). These and other

requirements seen as essential to new product development success are difficult to accomplish within the

context of alliances (Bidault and Cummings 1994).

Research Questions

Our paper aims to integrate these streams of research on product innovation and alliances in order

to compare internal new product development efforts (efforts conducted within an organization) with

external new product development (efforts undertaken within alliances). This problem has received only

limited attention from researchers and empirical work in this area has been exploratory in nature (cf. Bidault

and Cummings 1994; Littler et al 1995). By comparing and contrasting internal and external new product

development efforts we hope to identify advantages and disadvantages of alliance new product

development, specify conditions under which it might be more appropriate to conduct innovation internally

versus externally, and identify steps which firms could take to generate positive outcomes for external new

product development efforts.

Conceptual Model and Hypotheses

The litertiture on Nl?D is vast and varied in its focus (cf. Barclay 1992; Calantone, Benedetto,

and Divine 1992; Crawford 1991). Our research rests principally on the comprehensive model from

Zirger and Maidique (1990). Stemming from a research program they initiated in the early 1980s (see

2

There is some speculation that administrative mechanisms that serve well to manage these

uncertainties in alliance impair the new product development objectives. Indeed, Bidault and Cummings

( 1994) suggest that there is a fundamental clash between the “logic of innovation” and the “logic of

alliances.” Alliances succeed when goals and responsibilities of partners are clearly detailed (Hausler,

Hohn, and Lutz 1994; Lorange and Roos 1992). Innovation, however, requires a measure of flexibility to be

granted to those directly involved with the project. Alliance partners seek joint control of a project and

departures from prior agreements may involve renegotiation, and, thus may impede the flexibility required

for effective innovation. Organizations enter into alliances to take advantage of partners’ knowledge and

strength but most alliances are characterized by lack of trust (Lorange and Roos 1992). This restricts the

free flow of information, critical for new product success (e.g., Barclay 1992a, 1992b). These and other

requirements seen as essential to new product development success are difficult to accomplish within the

context of alliances (Bidault and Cummings 1994).

Research @restions

Our paper aims to integrate these streams of research on product innovation and alliances in order

to compare internal new product development efforts (efforts conducted within an organization) with

external new product development (efforts undertaken within alliances).This problem has received only

limited attention from researchers and empirical work in this area has been exploratory in nature (cf. Bidault

and Cummings 1994; Littler et al 1995). By comparing and contrasting internal and external new product

development efforts we hope to identify advantages and disadvantages of alliance new product

development, specify conditions under which it might be more appropriate to conduct innovation internally

versus externally, and identify steps which firms could take to generate positive outcomes for external new

product development efforts.

Conceptual Model and Hypotheses

The literature on NPD is vast and varied in its focus (cf. Barclay 1992; Calantone, Benedetto,

and Divine 1992; Crawford 1991). Our research rests principally on the comprehensive model from

Zirger and Maidique (1990). Stemming from a research program they initiated in the early 1980s (see

2

Maidique and Zirger 1985; 1984), the ZM model is a result of careful literature reviews, extensive case

research, and exploratory interviews involving 330 new products in the electronics industry. Their model

identifies the critical factors in both the internal and external environment of the organization, as well as

key activities for successful NPD.

There are two points we want to underscore before we present our adaptation of their model.

First, because the model is phenomenon centered, we should not be surprised that it uses perspectives

from many promising conceptual vantage points, including strategic management theory, resource

dependence theory, economics, and more. Their orientation is a good reference point for the approach in

the subject study. Our aims are not to test a single theoretical prescription or reconcile two theories, but

to use theory as a lens to examine the vexing phenomena of internal and alliance-based NPD.

Second, as you will see presently, we have consolidated a number of ZM model factors for

parsimony. This enables us to link conceptually and examine empirically the strategic alliances issues we

see in NPD. We only briefly treat our modest integrations because they are task oriented simplifications

rather than critical disputations. -

Successful NPD

ZM rely on strategic management theory in their propositions that strong R&D and marketing-

manufacturing prowess and coordination are critical for NPD success. Our adaptation brings together all

three functions. Indeed, many companies fail to bridge the barriers between functional areas and

information critical to a product’s formation and function gets lost. Besides communication difficulties,

lack of familiarity with another unit’s procedures and personnel can impede efficiency -- leaving some

tasks undone and others redone. Lastly, we look for a spirit of candor, teamwork, and reliance between

members of different units (cf., Song and Xie 1995; Souder 1981). Formally, we have:

hl: NPD success derives from competence in and coordination among R&D, marketing, and

manufacturing.

ZM verify research by Cooper (1979), Tushman and Romanelli (1985) and others that products

are more likely to be successful if they build upon a firm’s existing technologies and market strengths.

3

The logic of this factor of NPD pivots on the intersection of population ecology and learning theory:

New systems, technologies, personnel and customers can disrupt patterns of coordination and impair the

speed of the project. At the same time, firms enhance their survivability by doing what they do best in

the ecosystem that favors them. We have:

H2: NPD success is positively related to activities that fit and build upon core competencies.

ZM hypothesize that top management support is critical to the NFD process. They lean on

rudimentary leadership theory in their proposition that general management can provide the impetus for.

overcoming implicit barriers between functions, the requisite organizational resources, and a spirit of

commitment to NPD (cf., Booz Allen & Hamilton 1968). If we consider their logic more closely,

however, it seems clear that top management support is not so much expected to affect NPD directly, but

indirectly by influencing the level of effort and cooperation between units. We hypothesize:

h3: Competence and coordination among units in the NPD process derive from top

management support of the NPD effort.

The model also recognizes the criticality of customer knowledge and market standards in NPD.

Consistent with contemporary market-based management (Best 1997; Iohansson 1998), ZM reason that

successful NPD will derive from products that provide signz@ant value (Buzzell and Gale 1987).

Similarly, successful NPD results from products that offer $.mctiomZ and technical superiority over

competing products. We appreciate the practical utility of these variables as antecedents to NPD success

in the ZM model because they sharpen the customer focus of NPD efforts. Nevertheless, in our own pilot

research and in designing our cross-sectional sample survey, we encountered difficulty separating these

antecedents from the item domain of the criterion variable itself, NPD success. Thus, customer value and

functional/technical superiority are not exogenous variables in our adaptation of the ZM model; they are

indicators of NPD success.

Finally, the ZM model regards a focus on large and growing markets as a factor of NPD success.

A resource dependence perspective (cf. Aldrich 1979; Dwyer and Oh 1987) provides the conceptual

4

underpinning for this empirical reality. The subject study skirted examination of this sector of the ZM

model because our efforts to provide a more “sophisticated” analysis failed. Briefly, we thought

dimensions of predictability and uncertainty in the environment promised more intrigue than ZM’s

munificence variable, but our efforts to obtain good measures of environmental perceptions from

informants failed.’

Successful Alliances

The study of alliances is relatively recent, yet a body of empirical understanding has begun to

accumulate (cf. Varadarajan and Cunningham 1995). Although alliances have been formed for

distribution, product bundling, technology sharing and assorted other purposes, we will presume for the

time being that the factors of alliance success generalize to NPD goals. Thus, we will try to link the

veritable “checklist” of factors for alliance success to the model of new product success.

Trust and Communication: Organizations in alliances become vulnerable to the actions of partners whose

behavior is not under their control (Parkhe 1993). Participants in an alliance may not share one paramount

goal. Because partners enter into an alliance to maximize their own gains, it may be advantageous to seek

gains at the expense of the other partner (Parkhe 1993; Williamson 1985). Lack of trust is inherent and the

number one concern in alliances (Wolff 1994).

Trust exists when “one party has confidence in an exchange partner’s reliability and integrity”

(Morgan and Hunt 1994, p. 23). Predictability, dependability, and faith are three key components of trust

(Andaleeb 1992). In a study of vertical partnerships between manufacturers and dealers, Mohr and

Spekman (1994) found that more successful partnerships were characterized by greater levels of trust.

Kanter (1994) studied 37 companies from 11 counties and likewise found trust to be a key element in

alliance success. Conversely, Sherman (1992) found lack of trust to be a major cause of alliance failure.

Effective communication between partners is essential for alliance success. Communication refers

to “the formal as-well as informal sharing of meaningful and timely information between firms” (Anderson

and Narus 1990, p. 44). It enables goal adjustment, task coordination, and interfii learning. Mohr and

5

Spekman (1994) found that more successful partnerships exhibited better communication quality and

information sharing.

In the NPD process, trust seems to be a critical ingredient for interfunctional cooperation.

Although we sense that the relationship between trust, communication, and coordination is worthy of

considerable study in its own right, for our purposes, we need a more global construct. We will use a

midrange variable comprised of three interacting facets. Logically, coordination without communication

is fantasy, communication without trust is babble, and trust without coordination is empty. Similarly,

trust results from successful coordination and enables further coordination; communication arises from

and enables trust. We don’t claim that these three variables completely define a new abstract construct,

but will regard them in our study as three fairly compelling facets of an organizational syndrome we will

call cooperative competency2.

If we use the cooperative competency syndrome to capture the essence of ZM’s critical

antecedent to NPD success, the competence and coordination among units, we can make a pivotal

connection between the NPD and alliance literatures. This prompts us to reword hl:

Hl: NPD success derives from the cooperative competency among the functional and corporateunits involved.

We will now revisit one more hypothesis from the ZM model and develop five new hypotheses

involving antecedents to cooperative competency.

Resources. Alliances can be thwarted by the changing strategic priorities of partners. New priorities may

result in their not wanting to commit adequate resources to the alliance. And without adequate human,

financial, and other resources alliances will disintegrate or collapse (Lorange and Roos 1992). Gates (1993)

and Wolff (1994) suggest that the amount of resources each partner is to expected to commit should be

clearly laid out and understood by the other partner(s).

The commitment of resources to an alliance is akin to general management support of the NPD

effort in the ZM model.. Resource commitments are a manifestation of top management support of the

6

NPD effort, whether internally or in an alliance. Thus, the alliance literature suggests slightly different

operations of top management support, but the logic for h3-- now rephrased-- is the same:

H3: Cooperative competency among the functional and corporate units involved derives fromtop management support of the NJ?D effort.

Governance & Administrative IMechanisms. Strategic alliances are fundamentally an

interorganizational system applied to the process of NPD. Thus, as a governance mode, we should

observe alliance effects on NPD success primarily through cooperative competency. Following

institutional economics (cf. Williamson 1985) and generalizing from limitcd.empirical work (cf. Boyle et

al. 1992), internal NPD should outperform alliances on such criteria as inter-unit communication,

auditability, goal cohesion, and attitudinal solidarity. In terms of our model, we have:

H4: Cooperative competency is affected by governance structures in that internally conductedinnovation process provide higher levels of cooperative competency than in the NPD effortsof alliances.

Multifunction teams and alliances need administrative mechanisms that provide the parties with

a measure of certainty regarding roles and procedures, for making decisions, and for determining the

scope of participants providing input. Formalization, the use of explicit rules in the relationship, has

been identified as an impediment to the spontaneity and flexibility needed for internal innovation

(Bidault and Cummings 1994), but between firms tends to enhance effectiveness (cf., Dahlstrom, Dwyer

and Chandrashekaran 1995). Centralization, the concentration of decision-making authority, typically

impairs effectiveness as it increases perceptions of bureaucratic structuring which decreases favorability

of participants’ attitudes towards the project and results in increased opportunism (cf. John 1984). A clan

system is governed by shared values and norms. This common ground limits the needs for monitoring

and other bureaucratic devices and should enhance the abilities of the parties to work cooperatively.

Thus:

H5: Cooperative competency is positively affected by administrative mechanisms that are (a)formalized, (2) decentralized, and (3) clannish.

Fit. The success of strategic alliances depends critically on the strategic fit between the partners’ products,

markets, and objectives (cf. Gates 1993). When organizations enter into an alliance with similar but not

complementary motives conflict is likely to arise because of clash of interests and consequent opportunism

and lack of trust.

In the alliance literature one concrete question looms large in the discussion of fit: Are the

partners competitors? Competitors are apt to hold many common understandings of the market and

product development and production -- making for a good “fit.” But concerns about zero sum

opportunities, long-run partner motives, and the vulnerability of proprietary know how may seriously

impair “fit” (cf. Sheth and Parvatiyar 1992).

H6: Cooperative Competency in a NPD alliance is higher when the partners are noncompetitorsthan when they are competitors.

A second aspect of fit is the very nature of the innovation sought in the alliance. Radical--new to

the world-- innovations may tax existing systems of communication and patterns of collaboration more

than incremental innovation. Such innovations require greater outlay of resources and are riskier (Kotler

1997). Radical innovations are inherently more unpredictable opening up possibilities of conflicting

cultures (both interdepartmental and interorganizational). The “gate-keeping” approach in which new

-product development occurs in clearly defined stages is more difficult to accomplish in radical

innovation projects (cf. Song and Xie 1995). Thus:

H7: Cooperative Competency in NPD efforts is higher when the innovation is incremental thanwhen the innovation is radical.

Mutual Dependence. Alliances which are dominated by a single partner also typically have a very high

rate of failure (Cateora 1993; Gates 1993). The dominated partner typically stands to loose from such

arrangements and hence the high failure rate. Partners should safeguard their core competencies (Lorange‘. -

and Roos 1992) in order to discourage partners from breaking the rules governing the alliance. But as

McAlister, Bazerrnan and Fader (1986) explain, asymmetrical dependence interferes with joint problem

solving because the weaker is guarding against exploitation while the stronger tends to probe the

boundaries of exploitation or guard against the appearance of intentions to exploit. Of course, alliances

with low mutual dependence are not likely to show much cooperative competency, because exit or

neglect are real, viable options. Hence:

8

H8: Cooperative Competency in a NPD alliance is higher when the partners are highlymutually dependent than otherwise --i.e., when dependence is skewed or minimal.

Figure 1 summarizes our discussion and serves as a reference point for the eight formal

hypotheses. NPD success is our ultimate criterion variable in the model, and its principal antecedents (in

ovals) derive from Zirger and Maidique’s model. The boxed variables come from the alliance literature

and are hypothesized to impact NPD success through the variable cooperative competency, a midrange

construct and node in our model that has essential elements identified in both the alliance and NPD

literatures.

The Contexts for Theory Testing

Semiconductor Industry

Methodology

We chose the semiconductor industry as the primary context for our research. The semiconductor

industry (SIC code 3674) includes about 400 firms, including Digital Equipment Corporation, Intel,

Motorola, and Texas Instruments. This industry tends to be innovative and enters into a variety of

partnership agreements (Dutta and Weiss 1994). Technological innovation was identified as a top concern

for the 1990s by CEOs of US electronics industry and 50 percent of those surveyed indicated that they were

looking for research partnerships (Rayner 1991).

In one year alone, 130 alliance partnerships were reported in the semiconductor industry (U.S.

Industrial Outlook, 1993). For example, Advanced Micro Devices and Fujitsu have entered into an alliance

to develop a chip that can replace the hard disk drive in computers (New York Times 1992).

Demands from telecommunications, computer networking, automobile electronics, high-definition

TV, smart credit cards, and the personal computer industry make this industry competitive, innovative and

high-growth. (Standard and Poor 1994). The Semiconductor Chip Protection Act of 1984 protects a

semiconductor’s design for up to 10 years, thus providing an added incentive for innovation.

The Healthcare Sector

9

The healthcare sector, or more specifically “General Medical and Surgical Hospitals (SIC code

8062), ” was used a second context to replicate the hypotheses relating specifically to the introduction of

new services via alliances. About 30 percent of U.S. hospitals are members of alliances (Zuckerman and

D’Aunno 1990). Resource crunch, need for cost containment, need to be innovative, increased

interdependency between research and clinical service and changing disease patterns are prompting

hospitals to engage in alliances (Kaluzny and Sheps 1992).

Wrenn, Latour, and Calder (1994, p.53) point out that “the belief that hospitals are fundamentally

different in function and structure from for-profit, product producing companies has existed for some time.”

Mintzberg ( 1979) refers to hospitals as professional bureaucracies where exist a core of professionals with

a great degree of autonomy and power. Control in such organizations is based on bureaucracy and a system

of shared values. Thus, a replication in the hospital sector is a reasonable test of the generality of the theory.

Measures

Measures were developed and refined based on the guidelines provided by Churchill ( 1979) and

Gerbing and Anderson ( 1988). The relationship between alliance partners (for external product

development) and departments (for internal new product development) are the units of analysis for the

study. The Appendix presents the measures used in the study.

Product success refers to a product’s successful production, launch, and market acceptance.

Product success was measured using an eight-item scale that evaluates the new product on quality, financial

success, time-taken, market share, speed to market, and meeting of target costs. Cooper (1993) was used as a

guide to help specify the domain of this construct.

Trust is defined as the confidence an organization (or department) has in the ability and motivation

of the alliance partner (or other departments) to produce positive outcomes for the organization. The status

of measure development of this construct remains unsatisfactory (Andaleeb 1992; Sheth and Parvatiyar

1992). Our six-item measure of trust builds upon Mohr and Spekman (1994) and Morgan and Hunt (1994),

but includes an ability item and a reliability item.

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Communication is conceptualized to include the formal and informal sharing of timely, adequate,

critical, and proprietary information among alliance partners. We use a set of items modified from Mohr

and Spekman’s (1994) instrument. The communication measure is a five-item, five point Likert-type scale

that reflects communication quality (timeliness, and adequacy of information) and information sharing

(willingness to exchange critical, “proprietary” information).

“Coordination is often discussed but seldom measured” (Price and Mueller 186, p. 108).

Coordination is conceptualized as the extent to which activities, people, routines, and assignments work

together to accomplish overall objectives. We adapted Georgopoulos and Mann’s (1962) definition of

intraorganizational coordination, where coordination refers to the extent to which the alliance members (or

departments) function each according to the needs and requirements of the other parts and of the total

system. This definition is also consistent with Mohr and Spekman’s (1994, p. 138) definition that

coordination “reflects the set of tasks each party expects the other to perform.” A five-item measure

borrowed from Georgopoulos and Mann’s measure was modified to make it suitable for assessing

coordination in both interorganizational and interdepartmental settings.

Top management support was measured on a four-item five point scale with two items each for

clarity of agreement (the extent of clear-cut understanding about

side was expected to contribute) and lack of resistance (extent to

players in both organizations).

financial resources and manpower each

which there was no resistance from key

Three types of control mechanisms are examined. Centralization (the extent of concentration of

decision making); formulization (the extent to which explicit rules and procedures govern decision making);

ckan-control (the degree to which governance is conducted by shared values) (Ouchi 1980) were measured

using five-point Likert type scales (cf. Dwyer and Welsh 1985).

A competitor alliance is one where parties to the alliance are in either direct (e.g., an alliance

between two auto makers) or indirect competition (e.g., an alliance between a steel and plastic

manufacturer) outside the-relationship. A non-competitor alliance is one where parties to the alliance do not

vie for the same customers outside the relationship (e.g., an alliance between a manufacturer and a supplier

11

or between a manufacturer and a customer). A four-item Likert-type scale was used to classify the alliances

on these dimensions. Respondents were asked to indicate whether their partner was a competitor in the

same or different industry, a supplier, or a customer.

All innovations lie on a continuum of newness. We adopt the dichotomous classification of

innovations presented in the literature and classify all new products as incremental or radical. Radical

innovations are new-to-the-world pioneering products representing “technological breakthroughs.”

Incremental innovations refer to improvements and revisions to existing products, and additions to existing

product lines that supplement a company’s existing product lines (cf. Booz, Allen, and Hamilton 1982). A

four-item measure building upon Cooper (1993) is employed to classify innovations under one of these two

categories. An innovation was classified as radical if respondents indicated that the innovation was

pioneering, and did not directly build upon existing technology.

Mutual dependence is conceptualized from the Emersonian (1962) perspective i.e., the power of A

over B derives from B’s dependence on A. Our focus is on an alliance partner’s relative power-dependence

which is the difference between the dependency of the focal fm and its partner on the alliance. We employ

a modified version (modified to make it suitable for assessing dependence in alliances) of the instruments

used by Anderson and Narus (1990) and Boyle and Dwyer (1995). Two sets of four-item five point Likert-

type scales (both completed by the same informant) were used to measure the perceived relative dependence

of the alliance partners. Partnerships where both parties depended highly on the other and exhibited

marginal to no asymmetry in dependence (no difference in dependency of focal firm and its partner on the

alliance), were categorized as high mutually dependent relationships. Alliances exhibiting asymmetry in

dependence and those balanced at an insignificant level (both partners had low levels of power-dependence)

were classified otherwise.

Measure Purification

Depth interviews with key informants in four organizations and a jury of five advanced doctoral

students indicated that the questions were clear and relevant, except for one original trust item, which was

12

dropped. Overall the favorable comments of the panel and key informants, combined with prior use of

many measures, bwave us confidence going to the pilot test.

The Sampling Frame: The Semiconductor Context

A list of semiconductor firms with more than 20 employees was purchased from a leading

independent list compiler. The list contained names of 718 semiconductor firms, similar to numbers

reported by many other list compilers, but far greater than those reported in Manufacturing USA (457

semiconductor companies) and Ward’s Business Directory (346 semiconductor companies). After

eliminating what appeared to be multiple sites of the same company, sales offices, and small sub-contractors

there were 600 companies on the list. These 600 companies (the universe of semiconductor firms)

comprised the sampling frame.

The Pilot Test

We selected 150 companies on a 4th name basis for the pretest. These companies were contacted by

telephone to a) obtain the name of the key informant (i.e., head of the research and development

department), so that the survey could be addressed to that individual; b) prenotify this key informant about _

this survey and solicit participation; and c) verify the mailing address of the firm. Many of the smaller

companies did not have a formal R&D department, the function being assumed by the engineering

department. In these cases the contact person was either the President, CEO, or head of the engineering

department.

All questionnaires were mailed along with a cover letter and a $2 bill as incentive, and a first-class

postage paid return envelope. The cover letter explained the purpose of the survey and contained a non-

disclosure agreement indicating that the responses would be treated confidentially. Following Yu and

Cooper (1983) we used appeals that highlighted the importance of each response and the research. We also

offered to share the results in summary form if the informants so desired. A reminder/thank you card was

mailed 10 days after the questionnaire was mailed.

After four weeks, 40 completed surveys were received. This 28% response rate is comparable to

that reported in other studies on strategic alliances (e.g., Mohr and Spekman 1994; Parkhe 1993).

13

All measures had very high reliabilities with coefficient alpha greater than 0.80 in all cases. Using

Gerbing and Anderson’s (1988) paradigm all measures survived an exploratory factor analysis. In the

confirmatory factor analysis, although the chi-squares were significant, based on the maximum likelihood

factor loadings, GFTs, RMSRs, and normalized residuals we appear to have unidimensional, internally

consistent, and reliable measures.

Overall, our measures performed well and we made only minor modifications to some of the

measures for the main study. TO make the E-page instrument less burdensome, we trimmed one item each

from scales (for trust and communication) with coeffkient alpha greater than 0.90 (Devellis 1991). We

substantially revised the measure for radical/incremental innovation to enhance its content validity (the

measures retained for the main study are reported in the Appendix).

The Main Study

After using, 150 of the 600 semiconductor firms for the pilot study, we drew 350 for the main

study. Our sampling procedure attempted to include all publicly traded frnns (Compustat PC+ a Standard &

Poor database that lists all publicly traded fm was cross-referenced to identify publicly traded

semiconductor fmns), then f&ed in the rest on a random basis. The protocol for the main study was similar

to that of the pilot study beginning with telephone name verification and prenotification of the surveys.

The prenotification phase eliminated 68 for one of the following reasons: a) firms were not

semiconductor manufacturers; b) disconnected telephone number; c) company was no longer in business; d)

company was a sales or purchasing outfit only; e) R&D facilities were located in a foreign country; f)

company had a strict no-survey policy.

We sent 282 questionnaires using a protocol similar to the one used in the pilot study. The pilot

study suggested that many fm may not have entered into an alliance. Hence, the cover letter was changed

to encourage firms that had not entered into alliances to also respond to the survey. About four weeks after

the initial mailing, non-respondents were mailed a second copy of the questionnaire, thanking them if they

had already completed the survey and urging them to do so if they had not.

14

Of the 282 questionnaires mailed, 26 were returned because: a) the key informant declined to

participate in the survey; b) the company was not in the semiconductor business; or c) was in the

semiconductor business but did not manufacture semiconductors. In the end 95 completed responses were

received. Our 37% response rate compares favorably to those reported in other studies (e.g., Parkhe 1993).

Confirmatory Factor Analyses: Confirmatory Factor Analyses provided similar fit values to those reported

in the pilot data. Initially, separate single-factor models were evaluated for each of the constructs’ measures.

A separate four factor CFA model of trust, communication, coordination, and NPD success was run for

internal innovation measures. It was not possible to run CFA on alI measures in the study simultaneously

due to sample size constraints, because the ratio of sample size to the number of free parameters did not

approach the minimum 5: 1 requirements (cf. Bagozi and Baumgartner 1994).

Given that measures performed similarly in the pilot and final studies, we pooled the data for

hypotheses testing. The coefficient alpha reliabilities for the pooled data along with confirmatory factor

analysis are reported in

The factor loadings are

than 12.01

Table 13. These results provide evidence of unidimensionality of the constructs.

significant, indicating convergent validity. The normalizd residuals were a.lI less

[Insert Table 1 About Here]

Healthcare

As indicated earlier, the healthcare context was used as a second context to test the hypotheses to

make possible greater generalizability of the theory. Resource constraints allowed us to administer only a

truncated version of the semiconductor questionnaire for the healthcare context. Questions pertained only

to experiences with alliance innovation only; no questions were asked about internal innovation processes

for healthcare.

Using the same protocol as used in the semiconductor industry, 250 questionnaires were mailed out

to Chief Opera&g Officers in hospitals. We received 117 responses, of which 52 were from those who had

partaken in alliances. The measures performed very well in the healthcare context also with all measures

showing unidimensionality and having coefficient alpha greater than 0.70.

15

FINDINGS

A multiple regression analysis with new product success as the dependent variable was performed

to test hypotheses H 1 and H2 (please refer Table 2) As hypothesized in HI, new product development

success is positively associated with cooperative competency both in internally (b=.435, ~~01) and

externally (b=.385, p ~05) conducted projects in the semiconductor industry. These results also hold true

for the healthcare sector where also external NPD success is positively associated with cooperative

competency (b=.333, p<. 10).

Hypothesis H2 is supported in the semiconductor context, thus suggesting that NPD success is

associated with projects that build upon partners’ core competencies (b=.261, p<.O5) for the semiconductor

sector. In the health care industry results were not statistically significant.

[Insert Table 2 About Here]

Hypotheses H4 and H7 examined whether cooperative competency is impacted by governance

structure (innovation is conducted internally versus externally) and by the type of innovation (innovation is

radical or incremental). A 2 x 2 (governance structure x innovation type) ANOVA revealed significant

main effects for governance structure (F=9.10, p<.Ol) indicating support for H4. The absence of innovation

type main effects (F=2.41, p=. 12) and interaction effects (F=.470, p=.49) implies that H7 was not supported.

Thus a higher level of cooperative competency is observed in internal ( x =10.93) as opposed to external

( x =lO. 19) NPD projects. No statistically significant differences in cooperative competency are observed

in radical ( z =10.91) as opposed to incremental innovation projects ( x =10.47). Internal NPD executions

exhibited higher levels of cooperative competency than external NPD efforts for both radical ( x =l 1.09 vs.

10.61) as well as incremental ( x =10.84 vs. 10.01) innovation projects.

Table 3 provides the estimates of a multiple regression model of antecedents to coopertive

competency in alliances, in both research contexts.

16

Hypothesis H3 that cooperative competency derives from top management support was partially

supported (please refer Table 3). General management support is reflected in the quality of resources and

personnel allocated and priority accorded to the project by top management. We examined general

management support by examining clarity of agreement about resources to be provided to the project as well

as examining the (lack of) resistance of senior management to the project. Clarity of agreement about inputs

(bz.27 1, p<.O5) significantly enhances cooperative competency in the semiconductor industry. However,

lack of resistance from key players did not significantly contribute to cooperative competency in the

semiconductor sector. In the healthcare sector both independent variables-clarity of agreement (b=.287,

p<.O5) and lack of resistance from key players (b=.336, p<.O5) strongly influence cooperative competencies.

Thus overall H3 is supported in both contexts.

[Insert Table 3 About Here]

We attend to the same regression model used to test H3 in order to test our hypothesized effects on

cooperative competency from administrative mechanisms (H5), partner type (H6), and mutual dependence

(H8) on cooperative competency. As can be seen from Table 3, in the semiconductor industry, cooperative

competency is influenced by clan-oriented (b=.235, p<.O5) and formalized relationships (b=.252, p<.O5).

Though not statistically significant, cooperative competencies are negatively associated with high levels of

centralization. In the healthcare sector also cooperative competencies are positively associated with clan

oriented relationships (b=.256, pc.10) but not with formalized or decentralized administrative mechanisms.

Thus, overall H5 is partially supported.

Hypotheses H6 was not statistically significant in the semiconductor sector and could not be tested

in the healthcare sector since only 2 of the alliances were characterized by respondents as competitor

alliances. Thus, we cannot conclude that cooperative competency is affected by partner status as competitor

or non-competitor.

17

As hypothesized (HS), alliances with high mutual dependence exhibit greater levels of cooperative

competency in the semiconductor industry (b=.297, p<.Ol). Similar results were also obtained in the

healthcare sector (b=.2 14, p=. 10).

Before concluding our analysis, we tested two more models that broached the fundamental

propositions in our “alliance extension” of the ZM framework. Might the antecedents of cooperative

competency work directly-or indirectly through some unmeasured variable--on NPD success? We used

multiple regression analysis to test the effects of cooperative competency, mutual dependence,

administrative mechanisms (formalization, centralization, clan) and partner type on NPD success in both the

semiconductor and healthcare industries. In both sectors, only cooperative competency had a significant

impact on NPD success (b=.359, v.05 in healthcare) and (b=.520, p<.Ol) in the semiconductor sector.

None of the other predictors had a significant impact on NPD success though several of those predictors, as

previously discussed, have a significant impact on cooperative competency. A 2 x 2 Ancova Model of the

impact of governance structure (alliance conducted internally versus externally) and innovation type (radical

versus incremental) on NPD success (with cooperative competencies as covariate) indicated that projects

conducted internally have a higher success rate ( x =3.58 vs. 3.32), F=2.79, p<. 10. However, no significant

differences in success were observed between radical versus incremental innovation projects and no

interaction effects were also observed. Of course, cooperative competency had a significant impact on NPD

success (E52.4, p=.OOQ). Tables 4a and 4b report correlations among the variables presented above.

_

- [Insert Tables 4a and 4b About Here]

DISCUSSION

We examined the effectiveness of technology alliances against new product development efforts

conducted internally. Nearly 20,000 alliances were formed by US companies between 1988 and 1992 (Pekar

and Allio 1994). Given the growing popularity of alliances and the importance of managing the innovation

18

process, this attempt to integrate two different research streams is timely and significant. The central

objective was to isolate the advantages and disadvantages of alliances new product development.

As hypothesized, cooperative competency (a combination of trust, communication, and

coordination) contributes significantly to new product success for products developed internally as well as

for NPD carried out under alliances in two distinct contexts: semiconductor and health care.

AS hypothesized in H2, projects that build upon partners’ core competencies (fit) have a better

chance of succeeding. The logic of this factor stems from population ecology and learning theory: new. . .

systems can impair coordination patterns and fm enhance survivability by doing what they do best.

As hypothesized in H3, top management support can help foster cooperative competency. In OUT

study, management support was operationalized to include clarity of agreement and lack of resistance from

key players in both organizations. We find that clarity of agreement and lack of resistance from key players

fosters cooperative competency which in turn contributes to NPD success. However, clarity of agreement

about resources to be provided to the alliance and lack of resistance from key players do not directly ensure

alliance NPD success. The literature suggests that resistance from key players contributes to alliance failure.

Nevertheless, it is possible a different set of measures that directly focused on the amount of support

provided by top management (as opposed to the converse-resistance from key players) would have

demonstrated some impact on NPD success.

We found support for hypothesis H4 that cooperative competency is greater in internally conducted

projects than projects conducted in alliances. This effect was obtained in both contexts. Importantly, our

analysis in both the semiconductor and healthcare industries indicate that cooperative competency can be

enhanced in alliances by focusing on clarity of agreement about resources, overcoming resistance of key

players, and building the alliance upon partners’ core competencies.

Through their impact on cooperative competency, control mechanisms of the clan type contribute

most to new product success for projects conducted within alliances. Formalization seems to enhance

cooperative competency, while centralization is negatively associated with cooperative competency. This

support for H5 is an example of the conflict between the “logic of alliances” and the “logic of innovation.”

19

Prescriptions for successful alliance management (e.g., centralization) clash with prescriptions for

successful innovation management (e.g., autonomy to those directly involved with the R&D project). The

alliance literature suggests that strategic fit (a shared vision of the goals and objectives of those undertaking

the project) is important to overall project success. The present study suggests that the mechanism at work

is the type of control mechanism. Clan-type mechanisms best reflect a shared vision and values used to

guide behavior. Formalization mechanisms use procedures to guide behavior whilst centralization

mechanisms use decision-making authority to guide behavior.( .’

We were unable to conclude that cooperative competencies are higher in noncompetitor than

competitor alliances. This hypothesis, H6, could not be tested in the healthcare sector because only 2

alliances were identified as competitor alliances. Regarding H7, no significant differences are observed in

cooperative competencies in radical versus incremental innovations. These issues merit further study. It is

possible that while radical innovations may limit cooperative competencies due to the unpredictability and

greater risk of such enterprises, certain countervailing forces may operate to neutralize the tendency to limit

cooperation. Such factors might include the fact that radical innovation projects tend to be “star” projects

and take longer to complete, may provide unique mechanisms for building cooperative competencies.

As hypothesized in H8, cooperative competencies are greater when the partners are in a mutually

dependent relationship. Asymmetrical dependence or situations where the parties are not dependent on each

other are not conducive to a climate of cooperation. In the former case the weaker might be guarding

against exploitation. In the latter situation, minimal mutual dependence reduces the amount of commitment

parties have towards an alliance. It is easier for minimally dependent parties to ignore or walk away from

challenges than to hash out the means to continue to cooperate.

Innovations conducted internally have higher cooperative competencies and NPD success rates than

those conducted via alliances. Thus, while external NPD projects may allow for greater access to resources

and spread out risks (by sharing resources), such projects have lower success rates. Alliance NPD projects

should focus on ways to improve cooperative competencies in innovation projects. Clarity of agreement

and fit, partnering with mutuallydependent companies, and fostering clan and formalized relationships are

20

some mechanisms that organizations must pursue to maximize the chances of successful NPD in alliances.

As suggested by Bidault and Cummings (1994), some of the variables that limit cooperative competency

and consequently NPD success might be related to increased “managerial hurdles” and project costs that

tend to characterize alliances. These managerial hurdles which may reduce project speed, increase costs of

coordination, and reduce new product success might include lack of flexibility for those involved with the

project, conflicting priorities of senior management personnel within the companies, and a champion unable

to impact personnel and systems in both organizations.

Interestingly, while clear agreements, clans, formalization, and mutually-dependent relationships

directly impact cooperative competencies, these variables by themselves do not have a direct impact on

NPD success in either the semiconductor or healthcare contexts. Thus the key to NPD success in alliances

seems to be to build cooperative competencies. The key to building cooperative competencies is to have

clear-cut agreements, use clan and formalized control mechanisms, and engage in mutually dependent

partnerships.

Limitations

This study used the key informant method. Limitations of the key informant method have been

documented elsewhere (Philips 1981). Our respondents (senior R&D personnel in semiconductor firms and

Chief Administrators of hospitals) were well qualified to answer the research questions. But talking to more

than one informant within each organization may have yielded additional insights on interdepartmental

interactions during the new product development process. In the case of alliances, we just spoke to one

partner within the alliance. Talking to both partners, though a logistical challenge, would have yielded

“richer” insights and provided a more complete and “balanced” picture.

The alliances were evaluated after-the-fact by respondents. The study is based on the assumption

that trust, communication, and other variables studied lead to new product success. One might make a case

for the reverse, that success could have lead to inferences about trust and other variables studied (cf.

Canesan 1994). We attempted to control for this by trying to introduce variability in the type of project

21

selected. Respondents were asked to select the project that came to their attention most recently and not just

seiect successful or unsuccessful or “typical” projects.

The overall sample size of the study was limited for the healthcare context. In retrospect, because it

would have been more meaningful to have fully matched comparisons of internal versus external alliances

in two contexts, we lament our inability to secure the resources for a full replication in the healthcare sector.

Finally, most of our measures performed well, but a different approach to measuring environment

and top management support might have yielded additional insights.

Directions for Research.

Studies in new product development can be classified as a) generalist studies that identify key

variables that contribute to success and failure of new product development projects, or b) specific studies

that examine in depth one or more variables identified by the generalist studies (Craig and Hart 1992). This

research follows the generalist style and has tested a broad set of variables that contribute to the success and

failure of new product development carried out under technology alliances. Substantive issues that can be

tackled in future studies include a) how to make non-competitor and asymmetrically dependent alliances

work; b) other means of building cooperative competency in alliances; c) a more detailed development and

analysis of the cooperative competency syndrome; and d) what prompts alliance partners to use certain

types of administrative mechanisms and not other types. Bleeke and Ernst (1995) contend that unbalanced-

power alliances and competitor alliances are doomed to fail. However, because of the sparkling promise of

differential advantages many organizations are charmed into such alliances. Future research efforts should

focus on partner selection mechanisms undertaken by companies and how organizations can improve the

performance of competitor and imbalanced-power alliances.,

We also recommend that future studies, as posited by the ZM model, focus on favorability of the

environment rather than just knowledge of environmental conditions. If it is a less than munificent

environment that draws companies to form alliances, an understanding of the impact of environmental

factors on the behaviors of partners once they form an alliance would be very valuable. Other issues include

how prior experience with partnerships influences alliance management and what effects various structural

22

arrangements--e.g., is alliance located in own’s company or partner’s site, equity partnering, contractual

elements, communication systems-- have on the success of technology alliances. Clearly the work ahead

calls for many hands.

23

ENDNOTES

’ Our measures focused on whether organizations had adequate information about competitors,customers, suppliers, and government and their ability to predict changes in the environment. Thesewere not found to be associated with NPD success.

*In private correspondence Zirger agrees that trust as a facet of cooperative competency is needed forinternal NPD among the functional units.

3 CFA and coefficient alpha was computed only for items retained for the main study i.e., itemseliminated after the pilot test were not included in the pooled analysis.

24

Trust ItemsAppendix : Measures Used

Had the ability to contribute to the new product development effort.

Was capable of doing their part.

Had high integrity.

Could be counted on to do the right thing.

Motives could never be questioned.

We trusted that they would act in company’s best interests.

Communication Items

Alliance partner informed us of changing project needs.

Partner shared proprietary information with us.

Partner provided information that would help us.

Alliance partner provided us with adequate information.

Alliance partner provided us with timely information.

Coordination Items

The different job and work activities around the new product development activity fit together verywell.People from different organizations who had to work together did their job properly and efficientlywithout getting in each other’s way.

All related things and activities were well timed in the everyday routine of the innovation process.

The work assignments of the people from the different organizations who workedtogether were well planned.

In general, the routines of the different organizations that had to work with oneanother were well established.

25

Clarity of breement

The amount of financial resources each partner in the alliance was expected to contributetoward the new product development effort was clearly laid out.

The amount of manpower each partner in the alliance was expected to contributetoward the new product development effort was clearly laid out.

Fit

In retrospect, there was agood match between your company’s objectivesthe new product and that of your partner’s in developing the new product.

The product developmentexisting products.

effort benefited

for developing

its closeness to both company ‘S

Resistance from Key Players

There was no resistance to this alliance from key players in your organization.

There was no resistance to this alliance from key players in your alliance partner’s organization.

Mutual Power-Dependence

My alliance partner provided vital resources I would have found difficult toobtain elsewhere.

Much of the success or failure of the new product development effort can be attributedto my alliance partner.

It would have been difficult to replace my alliance partner.

The new product development effort would have suffered greatly if I had lost my alliancepartner.

Radical/Incremental

This was a unique new product project that did not directly build on technology of anexisting product or product line.

This project capitalized on existing technologytechnology existing within the company.

but represents a significant extension of

‘The product was pioneering, first of its kind (e.g., like the first personal computer or the firstwalkman or diet soda ever introduced in the market).

Similar products were available in the market when we introduced our product into the market.

26

NPD success

Product had superior quality and reliability.

Product is rated as a commercial success.

Product was killed, never went to the market.

Product was released on time.

(How would you rate the product on):

Financial performance

Market Share.

Time taken to introduce product into the market (idea to market).

Meeting of target costs.

Centralization

Problems in alliances are resolved hierarchically.

Even small matters in the alliance must be referred to someone higher up for an answer.

Formalization

We rely extensively upon contractual rules and policies in controlling day-to-dayoperation of the alliance.

We follow written procedures in most aspects of business in the alliance.

Clan

We trust the values and experiences of alliance members in controlling day-to-day activity.

We rely upon common values to guide day-to-day performance by alliance members.

Note: All Measures Were Parallely Phrased For Internal and External New Product Development. Allitems were phrased in L&r-t-type (strongly agree to strongly disagree) 5 point scale format except thelast 4 NPD success items which were measured on a five-point (very successfil to very unsuccessful)scale.

27

Table 1

Confirmatory Factor Analyses Results: Semiconductor Pooled Data

Measure (Object)

Trust (Internal)

Trust (Alliance)

Communication (Internal)

Communication (Alliance)

Coordination (Internal)

Coordination (Alliance)

NPD Success (Internal)

NPD Success (Alliance)

Chi-square

34.38,9 d.f., p=.OOO

35.59,9 d.f., p=.OOO

14.22,5 d.f., p=.O14

27.15,5 d.f., p=.OOO

12.3 1,5 d.f., p=.O3 1

18.13,5 d.f., p=.OO3

72.45,20 d.f., p=.OOO

84.23,20 d.f., p=.OOO ’

GFI A G F I RMSR

.916 .853 .05

.885 .799 .07

.960 ,941 .03

.885 .827 .06

.967 ,950 .02

.924 .886 .05

.868 .702 .09

.824 .604 .09

4 factor -trust, comm., 1705.42,246 d.f, p=.OOO .800 .750cord, npd success (internal)

no.ofitems6

6

5

5

5

5

8

8

.08 24

alpha

.87

.85

.88

.85

.89

.85

.78

.88

Note: All Items for Internal and External were parallely phrased.

28

Table 2

Multiple Regression Model of Success and various hypothesized predictorsStandardized Coefficients (t value)

Criterion Variables CooperativeComMencv

Fit R-Square F (P)

SemiconductorNPD success (internal) (n=116) .435 (5.16)** n/a .189 26.70 (BOO)NPD Success (alliance) (n=63) .385 (2.94)** .26 1 (2.00)* ,337 15.27 (BOO)

HealthcareNPD Success (n=41) .267 (1.55) ,063 (.371) .090 1.90 (. 163)

Note: one-tailed significance values are reported.* indicates significant at .05 level** indicates significance at .Ol leve+ indicates signficance at . 10 leveln/a indicates not applicable

29

Table 3

Multiple Regression Model of Cooperative Competency and various hypothesized predictorsStandardized Coefficients (t value)

Criterion Variables

Semiconductor(1~56)

CooperativeCompetency

Top Management Support

Clarity of Lack ofAgreement Resistance

.271(2.18)* .Ol(.lOS)

Administrative Mechanisms Competitor/ Radical/ Mutual Rsquare F ( p jNon Incremental Dependence

Formalization Centralization Clan

.252 (2.16)* -. 116 (-.942) .235 (1.99)* .036 (.334) .046 (.432) .297 (2.65)** .476 5.34(.W)

Healthcare (n=50)CooperativeCompetency

.287 (2.04)* .336 (2.23)* -.064 (-.461) -.074 (-.496) .256 (1.90)+ not tested -.132 (-.989) .214 (l&l)+ .375 3.61(03)

** indicates significant at .Ol level* indicates significant at .05 level+ indicates significance at .10 levelnot tested-only 2 of the health care alliances were competitor alliances and hence this was not tested.Note: Sample sizes indicated are smaller because items with missing values were excluded in the analysis.

We obtained similar results when we replaced missing values with means.

30

1. NPD Success-(I) 1.002. ‘. NPD Success-(A)3. Coop. Camp.-(I)4. Coop. Camp.-(A)5. Fit6. Clarity7. Lack Resistance8. Formalization9. Centralization10. Clan

a indicates significance at p=.Olb indicates significance at p=.O5

Table 4 aCorrelation Among Constructs: Semiconductor Industry (Pooled Data)

2 3 4 5 6 7 8

.32a1.00

.44a

.30a1.00

.08

.46a

.37a1.00

.08

.46a

.22

.57a1.00

.17

.26b

.15

.38a

.29b1.00

.03

.19

.Ol

.40a

.57a

.34a1.00

.ll

.ll

.20

.21-.09.19-.071.00

31

1. NPD Swcess2. Coop. Comp.3. Fit4. Clarity5. Lack Resistance6. Formalization7. Centralization8. Clan

Table 4 bCorrelation Among Constructs: Healthcare Industry

1 2 3 4 5 6 7 8

1.00 .3oc1.00

.18

.47a1.00

.17

.44a

.23c1.00

.005

.49a

.41a

.29b1.00

-.02.09-.03.28b.231.00

-.17.12.15.19.41a.40a1.00

.12

.23c-.37a.20.05.33a.0061.00

a indicates significant at p=.Olb. indicates significant at p=.O5c indicates significant at p=. 10

32

Figure 1

Governancestructure

Internal v.

alliance\

Administrativemechanisms:

DecentralizatbnFOllMliSm

C l a n I H4

rNcEs 1 H8 p.L& H1

/ H7I

I H8riMutual

I dependenceYes v. no

I

Innovationtype

Radical v.

incremental

NPD success

Builds on core

Adaptations from ZM model

11 Variables from the strategic alliances literature

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