the impact of alliance management capabilities on alliance attributes and performance: a literature...

The Impact of Alliance ManagementCapabilities on Alliance Attributes and

Performance: A Literature Review

Eva Niesten and Albert Jolink1

Copernicus Institute of Sustainable Development, Utrecht University, Heidelberglaan 2, 3584 CS, Utrecht, TheNetherlands, and 1Rotterdam School of Management, Erasmus University, PO Box 1738, 3000 DR Rotterdam, The

NetherlandsCorresponding author email: [email protected]

The literature on alliances has identified a variety of inter-firm antecedents of perfor-mance, including information and knowledge sharing between partners, sharedpartner understanding, and a focus on collective objectives. Recent studies havefocused on alliance management capabilities (AMC) – firms’ abilities to capture, share,store and apply alliance management knowledge – as an important antecedent ofperformance. This paper reviews 90 studies on AMC and makes two important con-tributions to the literature. First, the review provides an overview of and classificationscheme for the different types of AMC to better organise the diverse empirical findingsthat have been presented in the literature. The novel classification distinguishesbetween general and partner-specific AMC and between AMC stored within the firmand within the alliance. Second, consistent with the dynamic capabilities perspective,this paper offers a more detailed understanding of why AMC improve performance, byhighlighting the intermediate impact of AMC on alliance attributes. In particular, thereview demonstrates how the different categories of AMC influence alliances in termsof information and knowledge-sharing between partners, shared partner understand-ing and the pursuit of collective goals. The review also demonstrates that these attrib-utes improve performance. The authors note promising avenues for future empiricalresearch that involve combining the classification scheme with research on the impactof AMC on alliance attributes and performance.

Introduction

The recent literature on alliances has argued thatalliance management capabilities (AMC) are animportant antecedent of performance (e.g. Felleret al. 2013; Schreiner et al. 2009). Specifically, AMCrefer to the abilities of firms to capture, share and

store knowledge regarding alliance management andto apply this knowledge in ongoing and future alli-ances (Heimeriks and Duysters 2007; Kale andSingh 2007). Because capabilities are difficult oreven impossible to observe, researchers have identi-fied a large set of proxies that can be used to infer theexistence of AMC in firms (Godfrey and Hill 1995;Rothaermel and Deeds 2006), including structuraland process elements, such as specialized depart-ments, training, evaluation procedures, and codifiedtools (e.g. guidelines and contract templates)(Duysters et al. 1999; Kale et al. 2002; Kale andSingh 2007). These types of alliance-related

The authors would like to thank Koen Heimeriks, MarkoHekkert, Frank Wijen, participants of the 2013 BAM Con-ference, the Editor and three anonymous reviewers for theirhelpful and insightful comments on earlier drafts of thiswork.

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International Journal of Management Reviews, Vol. *, *–* (2014)DOI: 10.1111/ijmr.12037

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structures, processes and tools enable firms tocapture, share, store and apply alliance managementknowledge, and empirical research on AMC hasshown that firms with such capabilities demonstratebetter alliance performance than other firms (e.g.Heimeriks and Duysters 2007).

Studies on AMC frequently adopt a dynamic capa-bilities perspective (Teece et al. 1997; Vogel andGuettel 2013) and make theoretical claims that AMCare higher-order resources that influence the lower-order alliance-level resources (e.g. Schilke andGoerzen 2010; Sluyts et al. 2010). Examples of suchlower-order resources include various attributes ofthe alliance relationship, such as information andknowledge sharing between partners, shared partnerunderstanding and a focus on collective goals (e.g.Goerzen 2005; Hagedoorn et al. 2006). The theoreti-cal conjecture of studies on AMC is that AMCimprove alliance success, because such capabilitiesenable partners to adjust the attributes of the alliancerelationship based on environmental changes (e.g.Heimeriks and Schreiner 2010; Schilke and Goerzen2010). The empirical research on AMC has largelyfocused on explaining the variation in alliance per-formance by studying the structures, processes andtools associated with AMC; however, the empiricalliterature has not addressed the intermediate impactof AMC on alliance attributes. Several studies haveargued that a better understanding of how AMCinfluence performance is necessary and that such anunderstanding can be acquired by analysing howAMC influence alliance attributes and how theseattributes, in turn, affect performance (Heimeriksand Schreiner 2010; Rocha Gonçalves andConceição Gonçalves 2008; 2011).

This paper helps to develop a better understandingof the impact of AMC on performance by offeringthe first review of the literature examining AMC.This review is divided into two parts and presentsboth the empirical research on AMC and the theo-retical claims regarding how AMC influence allianceattributes. In the process, this study makes twoimportant contributions to the literature on AMC.First, based on a content analysis of 90 articles, weidentify and classify the proxies for AMC to organizethe diverse empirical findings in this field and todistinguish between different categories of AMC(Duriau et al. 2007). The resulting novel classifica-tion distinguishes proxies that capture, share andstore general AMC (i.e. knowledge about alliancemanagement that can be applied to any type of alli-ance, regardless of the type of partner) from those

that capture, share and store partner-specific AMC(i.e. knowledge about a specific alliance partner thatcan only be applied in future or concurrent allianceswith the same partner) (Al-Laham et al. 2008).Simultaneously, our novel classification distin-guishes proxies for AMC that are captured, sharedand stored within the firm from proxies for AMC thatare captured, shared and stored within the alliance(Ritala et al. 2009). This classification enables schol-ars to understand better the differences between cat-egories of AMC and will allow future studies to bemore explicit regarding the particular AMC categorythat is being studied and how this category affectsperformance. Second, we synthesize the claims thatthe literature makes regarding how AMC influencealliance attributes, and how these attributes in turninfluence performance. This review shows that theliterature most often refers to the impact of AMC onthe following three attributes: information andknowledge sharing between partners, shared partnerunderstanding, and a focus on collective goals. Thisreview summarizes the impact of AMC categories onthese three attributes and the impact of such attrib-utes on performance. This synthesis of theoreticalclaims not only highlights the importance of thedynamic capability literature examining AMC, butalso uncovers the intermediate impact of allianceattributes on the relationship between AMC and per-formance. This review calls for more empiricalresearch on the impact of AMC categories on alli-ance attributes and, subsequently, on performance.

This paper is structured as follows. The methodsection describes how the literature review was per-formed. The section on theoretical background andresearch design defines AMC and examines the theo-retical perspectives and the research designs of the90 articles included in this review. Next, we classifyAMC into four categories and examine the impact ofthese categories on various alliance attributes, inaddition to the impact of these attributes on perfor-mance. The final sections conclude, summarizeour contributions, and suggest avenues for futureresearch.

Method

We used content analysis to conduct the literaturereview, which is a ‘research method that uses a set ofprocedures to make valid inferences from text’(Weber 1990, p. 9). To make such inferences, weemployed material collection, descriptive analysis,

2 E. Niesten and A. Jolink

© 2014 British Academy of Management and John Wiley & Sons Ltd.

category selection and material evaluation (Mayring2008).

During the material collection phase, we selectedthe articles and book chapters for the literaturereview on AMC. We conducted an extensive searchfor scholarly peer-reviewed journal articles, using theEBSCO (Business Source Premier) article database.This database has strong coverage for the 25 journalswith the highest impact factors in the fields of busi-ness and management, and contains 98% of the bib-liographic records for these journals’ issues from thelast 20 years (Christoffersen 2013, p. 3). In theEBSCO database, we searched for the terms ‘alliancecapability’, ‘alliance capabilities’, ‘alliance manage-ment capability’, and ‘alliance management capabili-ties’. We searched for articles published between1998 and 2013, to include the article by Dyer andSingh (1998), which is frequently referenced as thefirst article to examine AMC specifically. This searchproduced 165 publications in academic journals. Toensure that we did not exclude any relevant articles inchoosing this 16-year time period, we performed anadditional search of the EBSCO database for theyears 1993–1998, using identical search terms,which produced no new articles regarding AMC.After carefully scanning the 165 articles, weincluded 78 articles in the study that specificallyaddress the subject of AMC. We excluded theremaining 87 articles, because they did not addressthe capabilities that are necessary to manage alli-ances; instead, these articles examined other capa-bilities, such as the marketing, manufacturing ortechnological capabilities that firms obtain by meansof their alliances with other firms. The excluded arti-cles typically referred to AMC only in their referencelists.

After reviewing these 78 articles, we added nineadditional articles and book chapters that we did notdiscover in our first EBSCO search. Several of theinitial 78 articles refer to these nine articles and bookchapters as relevant works on AMC. The new andlarger number of articles extended the time period to1997–2013, because we included Simonin (1997) onlearning about inter-firm cooperation. Five of thenine publications are not included in the EBSCOdatabase, because they are book chapters or werepublished in journals that are not included in theEBSCO database. The remaining four publicationsuse terms such as ‘alliance learning capability’, ‘alli-ance management competence’ or ‘alliance manage-ment skills’ to refer to AMC and, therefore, were notidentified in the first search. We performed a new

search in EBSCO using these three search terms.This search yielded three additional articles on alli-ance management skills, which we added to thisreview. In total, this review thus contains 90 articles,including the 78 articles from the first EBSCOsearch, the nine articles and book chapters that wediscovered using the snowballing method, and thethree articles we found by searching for ‘alliancemanagement skills’ (see Appendix 1 for the list ofarticles).

In the content analysis, we conducted a descriptiveanalysis of the theoretical perspectives and researchdesigns of the selected articles (Mayring 2008).Appendix 1 lists the theoretical perspectives of thearticles on AMC. Most of the articles adopt a capa-bilities perspective (48 out of 90 articles). In address-ing research design, we distinguished betweenarticles that present quantitative, qualitative and con-ceptual research. The majority of the articles in thisreview employ a quantitative research design (60%).Appendix 1 shows which articles are quantitative andindicates whether the hypotheses on AMC and per-formance are supported, not supported or partly sup-ported. Of the articles in this review, 22% use aqualitative research design, and 18% are conceptualarticles.

Next, during category selection, we organized thearticles included in this review in accordance withthe following topics: (1) we classified the proxies forAMC as proxies for general or partner-specific AMCand as proxies for AMC located within a firm orwithin an alliance; and (2) we determined the impactof AMC on alliance attributes and the impact of theseattributes on performance. We selected and com-bined the categories of AMC found in connectionwith the first topic based on the previous literature onalliances (e.g. Al-Laham et al. 2008; Lichtenthaler2008; Westney 1988; Zollo et al. 2002), but weinductively refined these categories while coding thereviewed literature (Duriau et al. 2007; Seuring andGold 2012). The proxies for AMC are the empiricaloperationalizations of the categories of AMC (Bailey1990; Seuring and Gold 2012). The patterns of rela-tionships that we identified with respect to the secondtopic were based on the existing theory of dynamiccapabilities, but the types of alliance attributes werederived from the articles under examination. Collec-tively, these articles most often refer to informationand knowledge sharing, shared partner understand-ing and a focus on collective goals as alliance attrib-utes that are influenced by AMC and that influenceperformance. Based on a close reading of the

Alliance Management Capabilities and Performance 3


articles, we determined which of the articles refer tothese attributes or to terms with similar content (seeFigures 1 and 2).1

Finally, during the material evaluation process, weensured the validity and reliability of the data analy-sis by having both authors code the text and allocateit to the topics and categories listed above (Weber1990). We also enhanced the validity of the dataanalysis by grounding the analysis in existing theoryregarding dynamic capabilities (Seuring and Gold2012).

Theoretical background and researchdesign of studies on AMC

An alliance management capability is defined as theability of a firm to capture knowledge regarding alli-ance management, to share and store this knowledgeand to apply this knowledge in ongoing and futurealliances (e.g. Kale and Singh 2007). Firms captureand accumulate knowledge about alliance manage-ment by effectively using their experience with alli-ances and by translating this experience intoknowledge (e.g. Anand and Khanna 2000; Simonin1997). Through their experience with alliances, firmslearn how to manage such arrangements, and theydevelop AMC as a result (e.g. Heimeriks andDuysters 2007). Firms also develop AMC by imple-menting structures and processes designed specifi-cally for alliances, such as specialized departments,training and evaluation procedures (e.g. Hoffmann2005; Schilke and Goerzen 2010; Sluyts et al. 2010).Firms also use codified alliance tools, such as guide-lines or contract templates, and they hire externalspecialists to capture and apply alliance managementknowledge (Kale and Singh 2009; Sluyts et al.2010). These structures, processes and tools enablefirms to capture, share, store and apply alliance man-agement knowledge. Alliance management capabili-ties have been defined as those abilities that allowfirms to improve the management of individual alli-ances, but have also been understood to allow firms

to manage their alliance portfolios (e.g. Hoffmann2005; Lavie et al. 2007; Parise and Henderson 2001;Sarkar et al. 2009). Wassmer (2010) refers to thesetwo types of capabilities, distinguishing single AMCfrom alliance portfolio management capabilities, butleaves it to future empirical research to disentanglethe different attributes embodied in these two typesof capabilities. As of the date of this writing, theliterature has focused primarily on the skills requiredto successfully manage a single alliance (Kale andSingh 2009).

Theoretical perspectives

Various theoretical perspectives have been used tostudy AMC, such as the dynamic capabilitiesperspective, organizational learning theory, theknowledge-based and resource-based views, andevolutionary economics (Wassmer 2010). In Appen-dix 1, we illustrate this diversity by listing the theo-ries and the literature that are cited in the articles inthis review. The majority of the articles study AMCusing a capabilities perspective, and several studiesargue that AMC can be considered a type ofdynamic capability (e.g. Chang et al. 2008; Schilkeand Goerzen 2010). In a bibliometric review of theliterature on dynamic capabilities, Vogel andGuettel (2013) find that the articles on alliancecapabilities form an important and separate clusterin the larger research field of dynamic capabilities.Teece et al. (1997, p. 516) define dynamic capabili-ties as ‘a firm’s ability to integrate, build, andreconfigure internal and external competences toaddress rapidly changing environments’. Thesecapabilities include the firm’s ability to adjust itsroutines, resources, and competences to adapt tochanges in the environment (Draulans et al. 2003;Rothaermel and Deeds 2006). Such capabilities arefrequently referred to as higher-order or first-orderresources that can alter lower-order or second-orderresources (Eisenhardt and Martin 2000). The word‘dynamic’ in the term ‘dynamic capability’, refers tointentional changes in or renewal of lower-orderresources (Ambrosini and Bowman 2009). Becauseof this divide between higher-order and lower-orderresources, dynamic capabilities are only indirectlylinked with performance: dynamic capabilities aimto change a firm’s bundle of resources, routines andcompetencies, which in turn affect economic perfor-mance (Eisenhardt and Martin 2000; Zott 2003).The resource base is directly linked to rents, butbecause dynamic capabilities are one step removed

1Information- and knowledge-sharing also includes commu-nication, the exchange and transfer of information andknowledge, and information and knowledge flows. Sharedpartner understanding also includes mutual and commonunderstanding, shared values and norms, and shared andaligned expectations with respect to the alliance. Collectivegoals include collective objectives and purpose with respectto the alliance and mutual, common, symmetrical, andaligned goals and objectives.



from rent generation, their effect on rents is onlyindirect (Ambrosini and Bowman 2009).

Studies on AMC propose that AMC are higher-order resources that enable changes to the attributes ofthe alliance, which are considered lower-orderresources (e.g. Heimeriks and Schreiner 2010; RochaGonçalves and Conceição Gonçalves 2008; 2011;Schilke and Goerzen 2010). In Appendix 1, we indi-cate which articles viewAMC as dynamic capabilitiesand refer to AMC as higher-order resources (see foot-note c to the Appendix). For instance, Heimeriks andSchreiner (2010, p. 148) describe AMC as higher-level resources and argue that ‘the theoretical mecha-nisms by which alliance capabilities affect allianceperformance can only be clarified by taking intoaccount what happens at the dyadic level of the alli-ance’.The theoretical conjecture is thatAMC improvealliance success because they allow partners to adjustthe attributes of the alliance to changes in theenvironment (e.g. Heimeriks and Schreiner 2010;Schilke and Goerzen 2010). Examples of lower-order resources in an alliance that have a beneficialimpact on performance include information- andknowledge-sharing between partners, shared partnerunderstanding, and the pursuit of collective objectives(e.g. Pavlovich and Corner 2006; Spralls et al. 2011).Several studies onAMC indicate that alliance partnersuse their AMC to alter lower-order resources in thealliance in response to environmental changes (e.g.Hoffmann 2005; Rocha Gonçalves and ConceiçãoGonçalves 2008; 2011; Spralls et al. 2011). Alliancemanagement capabilities thus improve performancebecause they enable partners to adapt the type ofinformation and knowledge that is shared within thealliance, their shared understanding, and the collec-tive objectives, to environmental changes. Sampson(2005, p. 1028) argues that the positive link betweenrecent alliance experience and performance reflectsthe importance of dynamic capabilities:

[W]hat matters to a firm’s ability to benefit fromcollaboration is not a long history of alliance expe-rience, but recent experience, signaling the impor-tance of adaptations to the current competitiveenvironment. Dynamic capabilities may take theform of the specialized alliance managementoffices, involving specialized personnel who arecommitted full time to their change roles.

Research designs

The majority of the articles in this review employquantitative research methods to study AMC.

Because capabilities are difficult or even impossibleto observe (Godfrey and Hill 1995; Rothaermel andDeeds 2006), researchers use a variety of proxies tomeasure AMC. These proxies include alliance struc-tures and processes such as specialized departments,managers, training, and codified tools such as guide-lines, contract templates and databases (e.g. Kaleet al. 2001). Appendix 1 offers an overview of theproxies that are used by the articles in this review.Studies on AMC assume that firms will have devel-oped AMC when they have specialized alliancedepartments and train their managers or codifyknowledge in specialized alliance guidelines(Schreiner et al. 2009). Studies characterize the vari-ation in alliance performance as a function of thenumber of alliance structures, processes and toolsthat firms possess (e.g. Heimeriks et al. 2007, 2009).

Alliance performance is measured in a variety ofways. One stream of the literature focuses on finan-cial gains, such as profits, sales or abnormal stockmarket returns after announcements of alliances(Anand and Khanna 2000; Lambe et al. 2002; RochaGonçalves and Conceição Gonçalves 2008; 2011). Asmall number of studies measure the innovativeoutput of firms or alliances (Anderson et al. 2011;Cui and O’Connor 2012). Another stream of the lit-erature measures success using evaluations in whichmanagers are asked to rate the extent to which thecompetitive position of the firm has improved as aresult of the alliance or the extent to which the firmhas acquired skills from its alliance partner(Draulans et al. 2003; Heimeriks and Duysters 2007;Heimeriks et al. 2009; Kale and Singh 2007; Schilkeand Goerzen 2010; Schreiner et al. 2009; Zollo et al.2002). These various ways of measuring perfor-mance are not specific to the field of AMC, but arealso employed in the literature that focuses on theinter-firm antecedents of alliance performance(Christoffersen 2013, pp. 4–5). Most quantitativestudies of AMC demonstrate that there is a positiverelationship between alliance performance and theuse of specialized structures, processes and tools.The fourth column in Appendix 1 offers a detailedoverview of the relationship between AMC and per-formance for each article in this review.

The majority of these quantitative studies on AMCadopt a capabilities perspective and view AMCas dynamic capabilities and, thus, as higher-orderresources that influence resources at the alliancelevel (e.g. Al-Laham et al. 2008; Chang et al. 2008;Heimeriks et al. 2007, 2009; Kale et al. 2002; Kaleand Singh 2007; Lambe et al. 2002). However, these



studies do not empirically research the effect ofAMC on the attributes of alliances to determine theimpact of AMC on performance. Instead, sucharticles primarily elaborate on the expected impact ofAMC on alliance attributes in their introduction anddiscussion sections, whereas the empirical researchthat is conducted does not address the impact ofAMC as higher-order resources on lower-orderresources in alliances.

The review of the literature on AMC also includesqualitative case studies and conceptual articles onAMC. Several of these articles also view AMC ashigher-order resources that influence lower-orderresources in alliance relationships, but they do notreport on empirical research that links AMC to alli-ance attributes (Kind and Knyphausen-Aufseß 2007;Naqshbandi and Kaur 2011; Sluyts et al. 2010).

In the remainder of this paper, we first review theempirical (and mostly quantitative) findings in theliterature on AMC by arranging the empirical proxiesinto four categories of AMC. Second, we synthesizethe theoretical conjectures regarding how these fourcategories influence alliance attributes and how theattributes affect performance. By linking these twoelements of the literature on AMC, we are able tooffer valuable suggestions for future research inwhich empirical studies can focus on the relationshipbetween categories of AMC and alliance attributes.

A classification of proxies for alliancemanagement capabilities

Based on the literature review, we distinguishbetween three types of proxies for AMC: alliancestructures, alliance processes and alliance tools (seeTable 1 and Appendix 1) (e.g. Kale and Singh 2007,2009). Alliance structures consist of organizationalunits and the relationships between them. These unitsare dedicated to capturing, sharing, storing andapplying alliance knowledge and may include alli-ance departments, managers and teams (Heimerikset al. 2007; Kale et al. 2001). Alliance processesinclude the debriefing and rotation of alliance man-agers, forums and networks for formal and informalknowledge-sharing, training and evaluation proce-dures (Kale and Singh 2007). These processes incor-porate the best practices – based on allianceexperience – to capture knowledge and stimulate thesharing of (often tacit) knowledge between partnersand between employees. Alliance tools includemanuals, guidelines, templates, databases, and

contact lists that capture, share, store, and applycodified alliance knowledge (e.g. Sluyts et al. 2011).

We classify these proxies as proxies for general orpartner-specific AMC and as proxies for AMC thatare stored within the firm or within the alliance.Zollo et al. (2002) refer to the former as a distinctionbetween how firms learn to handle the complexitiesof the alliance process and how they learn about thepartnering firms themselves. General AMC are basedon alliance management knowledge that is obtainedfrom experience with different partners and that maybe useful in future alliances regardless of the type ofpartner. Partner-specific AMC include the ability offirms to capture, share and store knowledge about aspecific alliance partner; these abilities can be uti-lized in consecutive alliances with the same partner(e.g. Al-Laham et al. 2008). Westney (1988, p. 344)refers to the second distinction as distinguishingbetween the two dimensions of cooperative strate-gies: the transfer of learning within a firm and themanagement of relationships between partners. Alli-ance management capabilities are not stored exclu-sively at the firm level; instead, they are also retainedoutside the boundaries of the firm and stored at thealliance level (Lichtenthaler 2008; Ritala et al.2009). Although several studies discuss the distinc-tion between general and partner-specific AMC, onthe one hand, and between capabilities within thefirm and within the alliance, on the other, we offer thefirst classification in which these two distinctions arecombined to generate four categories of AMC.

This classification of AMC combines the concep-tual and the empirical level (Bailey 1990) such thatwe present a conceptual classification of the fourcategories of AMC and provide empirical examplesof these categories, which are proxies for AMC.These proxies represent the different ways in whichresearchers have attempted to measure AMC and cantherefore also be referred to as indicators (Bailey1994). We use Bush and Hunt’s requirements forclassification schemes2 to evaluate the classification.In general, we believe that this classification is par-ticularly useful for research examining AMC and,more generally, in the field of dynamic capabilities(Bush and Hunt 2011). Classifying AMC into fourcategories allows us to organize the diverse objects of

2‘Usefulness; mutual exclusivity; collective exhaustiveness;whether the scheme adequately specifies the phenomena tobe classified; and whether the scheme adequately specifiescharacteristics that will be doing the classifying’ (Bush andHunt 2011, p. 81).



analysis of the studies on AMC and offers a startingpoint for future empirical research that might analysehow the mechanisms of each category explain theimpact of AMC on alliance attributes. This classifi-cation of AMC meets the requirements of mutualexclusivity and collective exhaustiveness. Table 1presents the proxies in each of the four categories:general AMC within the firm; partner-specific AMCwithin the firm; general AMC within the alliance;and partner-specific AMC within the alliance. Thenumbers in these four categories refer to the articlesthat discuss each AMC category; both the numbersand the corresponding articles can be found inAppendix 1. The following sections discuss the four

categories and the proxies in detail to confirm thatthis classification adequately specifies the proxiesand the four categories of AMC.

General alliance management capabilitieswithin the firm

The general AMC within a firm include a firm’sability to capture, share and store alliance manage-ment knowledge and to apply that knowledge tothe firm’s current and future alliances regardlessof partner type. These AMC are developed bygenerating structures, implementing processesand creating tools that are all related to alliances.

Table 1. Classification of proxies for AMCa

General AMC Partner-specific AMC

Withinthe firm

1. Structures: Corporate alliance office; vice-president ordirector of alliances; alliance (management) team; alliancedepartment; alliance manager; alliance sponsor, alliancespecialist; alliance gatekeeper; alliance committees andtaskforces.

Processes: Debriefing of alliance managers; record-keepingand reporting on incidents, decisions and performance ofalliances; rotation of alliance managers; rewards for alliancemanagers; forums and networks for (in)formal knowledgeexchange; internal alliance training; alliance seminars andworkshops; individual and cross-alliance evaluations.

Tools: Alliance guidelines; worksheets; manuals; checklists;metrics; templates for partner selection, alliance negotiationand alliance contracts; assessment tools to evaluate partnerfit; database with factual information on alliances;simulations; logbook; contact list; intranet.

References: 1, 2, 3, 4, 6, 8, 9, 11, 13, 15, 16, 17, 18, 19, 20,21, 22, 23, 24, 26, 27, 28, 29, 30, 32, 33, 34, 36, 37, 38, 39,40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 54, 56, 58, 62,64, 65, 67, 70, 71, 72, 73, 76, 77, 78, 79, 81, 82, 83, 84, 85,87, 88, 89, 90.

2. Structures: Alliance management office; alliancedirector; alliance manager; stable role definitions forboundary spanners; firm’s ability to contract withspecific alliance partner.

Processes: Informal and formal processes for sharingknowledge on alliance partner; brainstorming sessions;internal alliance training.

Tools: Database with factual information on alliancepartners; intranet; implementation manuals.

References: 27, 66, 75, 76, 89.Partner-specific experience: 24, 43, 55, 60, 62, 66, 68, 75,

76, 90.

Within thealliance

3. Structures: Alliance manager, alliance specialist orcommunication system in joint venture; joint teams ofalliance partners; alliance review committee; cross-companymanagement team; inter-firm taskforce.

Processes: External alliance training; use of external alliancespecialist: consultants, lawyers, mediators and financialexperts; joint business planning; joint evaluation; meetingevents in partner programme.

Tools: Alliance contract as repository of alliance knowledge;shared intranet; virtual team room; directory with contactdetails and repository with alliance documents.

References: 2, 5, 18, 24, 27, 39, 40, 41, 42, 50, 51, 52, 62, 67,75, 79, 80, 83, 84.

4. Structures: Alliance review committee; joint teams ofalliance partners; channels of communication;partner-specific interfaces; alliance specialist in jointventure; inter-firm taskforce.

Processes: Routines for inter-firm partner-specificknowledge sharing; joint business planning; jointalliance evaluation; partner programme; shared strategydiscussion; process development meeting; relationshipsteering group meeting.

Tools: Memorandum of understanding; alliance contractas repository of alliance knowledge; virtual team roomand web-conferencing; directory with contact detailsand repository with alliance documents;communications matrix; shared intranet.

References: 3, 4, 12, 24, 26, 30, 33, 39, 40, 41, 42, 43, 47,49, 50, 51, 53, 55, 57, 61, 62, 66, 67, 68, 75, 80, 83, 84,90.

aNumbers refer to the articles in Appendix 1.



Alliance structures can be quite developed in largefirms, and may include a corporate alliance depart-ment that (or vice-president who) oversees alliancemanagers across the different departments of the firm(Hoffmann 2005; Kale et al. 2001). Such alliancemanagers are responsible for several teams thattransfer alliance knowledge both between theseteams and to the alliances in which these teams areengaged (Kale et al. 2001; Mascarenhas and Koza2008; Sampson 2005). Smaller firms may employ analliance specialist or a few officers who are respon-sible for managing alliance knowledge (Draulanset al. 2003; Heimeriks and Duysters 2007; Hoangand Rothaermel 2005; Wittmann 2007). When firmsemploy alliance specialists, their alliances are moresuccessful, but only when the specialists areemployed near the location in which the alliances aresituated and when the specialist is not part of thesenior management team (Draulans et al. 2003).

Examples of alliance processes include coachingmanagers in alliance skills, developing employeetraining programmes, sharing tacit knowledge ininternal networks and forums, and evaluating thealliance processes themselves (De Man and Duysters2005; Kale et al. 2001, 2002). Draulans et al. (2003)report that a manager’s ability to compare and evalu-ate alliances contributes positively to their success.When alliances are compared frequently accordingto a set method, more people are likely to be involvedin the evaluation process, and alliance knowledgewill be more widely distributed within the firm.

Alliance tools provide codified knowledge regard-ing alliance management. Such tools include man-agement guidelines, worksheets, manuals andtemplates that assist managers with specific aspectsof alliances, such as partner selection and assess-ment, negotiations and the development of contracts(Kale et al. 2001, p. 465). Hoang and Rothaermel(2005, p. 333) refer to diagnostic tools and simula-tions as important elements of the codification of keyinsights that are gained through reflection on pastalliance experiences. Firms may also maintain data-bases that contain factual information on each oftheir alliances, such as the date and purpose of for-mation, names of partners and of managing execu-tives (Kale and Singh 2007, p. 999).

Partner-specific alliance management capabilitieswithin the firm

Most alliance structures, processes and tools thatare relevant to developing general AMC within a

firm may also be relevant to developing partner-specific AMC within a firm. The difference is thatthe structures, processes and tools for partner-specific AMC only capture, share and store alliancemanagement knowledge that is specific to a particu-lar partner and that can only be applied in alliancesinvolving this same partner. The articles in thisreview refer to managers, training, informal andformal processes, databases and manuals, and anintranet as proxies for partner-specific AMC thatcapture, share and store knowledge on specific part-ners within a firm (e.g. Dyer et al. 2001; Zollo et al.2002). Different departments within a firm may beengaged in different alliances with the samepartner. Alliance managers develop partner-specificAMC within a firm by transferring knowledgeabout a partner between the firm’s different depart-ments. Pangarkar (2004) discusses firms thatemploy ‘boundary spanners’ for concurrent or con-secutive alliances with the same partner. Boundaryspanners are alliance managers who transfer knowl-edge about a specific partner into the firm. Ryalland Sampson (2006) discuss the ability to contractalliances as a particular type of firm-level, partner-specific AMC. They demonstrate that firms thatenter into consecutive alliances with the samepartner improve their ability to write more detailedcontracts with that partner at lower costs. Thesefirms develop contracting capabilities because theylearn more about their partners as they accrue addi-tional experience contracting with them (Ryall andSampson 2006).

In informal and formal processes and in internaltraining sessions, alliance managers and employeescan share knowledge within the firm regarding aparticular partner (e.g. Dyer et al. 2001).

Using alliance databases and manuals, in additionto intranets, firms store codified knowledge aboutalliances with particular alliance partners, such asfactual information regarding events, decisions andactions taken in these alliances (Duysters et al.2012).

General alliance management capabilities withinthe alliance

General AMC may also be captured, shared, storedand applied within the alliance rather than internal-ized within the firm. Alliance partners may decideto create a joint review committee or a cross-company management team to capture, share,store and apply knowledge regarding alliance



management within the alliance (Kale and Singh2009; Schreiner et al. 2009). When an alliance isstructured as a joint venture, the partners maydecide to hire an alliance specialist to address theshared ownership portion of the joint venture(Albers 2010), i.e. an individual who is responsiblefor storing, codifying and disseminating know-ledge on alliance management within the jointventure.

Alliance partners may also agree to hire an exter-nal specialist or to register for specialized externaltraining when they do not have access to allianceknowledge within their respective firms (De Man2005). External parties who supply general alliancemanagement knowledge might include consultants,lawyers, mediators and financial experts (Heimeriksand Duysters 2007; Heimeriks et al. 2009; Sluytset al. 2010). Various external parties may behired during different stages of the alliance lifecycle (Kale and Singh 2009). Thus, lawyersmay be involved in the formation stage, whencontracts must be drafted and signed, whereasmediators may be hired to resolve conflictsbetween partners in the post-formation stage(De Man 2005; Duysters et al. 2012; Sluyts et al.2010).

General AMC may also be stored within analliance as codified alliance knowledge. Usinga shared intranet (or extranet), partners can assem-ble a repository of alliance documents, guide-lines and manuals (Parise and Casher 2003).Furthermore, alliance knowledge can be incorpo-rated in alliance contracts that are adjustedover time to incorporate such knowledge andbecome ‘repositories for knowledge about how togovern collaborations’ (Mayer and Argyres 2004,p. 394).

Partner-specific alliance management capabilitieswithin the alliance

Alliance partners may also capture, share, store andapply partner-specific AMC within the alliance.Partner-specific AMC allow the effective use ofknowledge about a specific partner that has devel-oped over time and is stored within the alliance overthe course of multiple consecutive alliances with thatsame partner (Zollo et al. 2002). Partners that engagein repeat alliances capture knowledge about oneanother in different ways. They may capture, shareand store partner-specific knowledge in inter-organizational structures that are used in consecutive

alliances with repeat partners. Some examples ofthese inter-organizational structures include jointteams of alliance partners, channels of communica-tion and partner-specific interfaces (Hoang andRothaermel 2005; Kale and Singh 2007; Khalid andLarimo 2012).

Repeat partners may also develop inter-firm rou-tines that capture, share, and store partner-specificknowledge (Dyer and Singh 1998; Hoang andRothaermel 2005; Kalaignanam et al. 2007; Kaleet al. 2002; Kale and Singh 2007; Kim et al. 2006;Mayer and Argyres 2004; Parise and Henderson2001). Zollo et al. (2002, p. 701) define these inter-firm routines as ‘stable patterns of interactionbetween two firms that are developed and refined inthe course of repeated interactions’. In these rou-tines, repeat partners exchange knowledge aboutthemselves and develop a more refined understand-ing of the other’s cultures, management systems,capabilities, weaknesses, behaviours and beliefs,while storing that information for future use (Zolloet al. 2002). These routines enhance the effective-ness of inter-firm agreements and strengthen inter-action between repeat partners (Zollo et al. 2002, p.701, 703). Kohtamäki et al. (2013) refer to sharedstrategy discussions, process development meetingsand relationship-steering group meetings as pro-cesses in which repeat partners might share andstore partner-specific knowledge that will benefitthe alliance.

To facilitate the sharing of codified partner-specific knowledge, repeat partners may transferinformation through a shared intranet and store it inboth a directory with the contact details of the part-ners and a repository with alliance-related docu-ments (Heimeriks and Schreiner 2010; Parise andCasher 2003). Repeat partners may create a memo-randum of understanding in which they specify theirdesired goals, expected outcomes and the responsi-bilities and tasks of the respective partners(Mascarenhas and Koza 2008). This memorandummay be altered over time to convey and/or memori-alize new perspectives and ideas. Dyer and Singh(1998) provide an example of a partner-specific alli-ance tool that was implemented by Xerox and Fuji.These two firms developed a communications matrixthat identifies a set of relevant issues in the alliance(e.g. products, technologies, markets) and thenmatches individuals by function to the appropriatematters, which allows an employee of one firm toinstantly find the proper contact person at the partnerfirm.



Relationships between AMC, allianceattributes and performance

In this section, we discuss the relationships betweenthe four categories of AMC and alliance attributes, inaddition to the relationships between attributes andperformance. In particular, we synthesize the theo-retical conjectures found in the literature review.Based on a content analysis, we establish that theliterature most often refers to the following threealliance attributes: information and knowledgesharing between partners; shared partner understand-ing; and a focus on collective objectives (e.g.Pavlovich and Corner 2006; Spralls et al. 2011).Figures 1 and 2 summarize the impact of the fourAMC categories on these three alliance attributesand the impact of these attributes on performance;these figures indicate which articles in this reviewfocus on a particular type of relationship.

General AMC within the firm, alliance attributesand performance

Many of the articles in this review discuss the ben-eficial impact of general AMC within the firm oninformation and know-how sharing between partners(A1 in Figure 1). The distinction between knowledgeof alliance management (i.e. general AMC) andcontent knowledge is important in this regard. Firmswith knowledge of alliance management are betterable to stimulate the transfer of information andknow-how about the content of the alliance, i.e.information or know-how about the alliance’s prod-ucts, activities and technologies (Grunwald andKieser 2007). Following Dyer and Singh (1998,p. 665), information is defined as easily codifiableknowledge, whereas know-how involves knowledgethat is complex and difficult to codify. Although theinformation that partners share in an alliance can bequite diverse, most partners must share certainsimilar types of information during the life cycle ofthe alliance (Kale and Singh 2009). During the earlystages of negotiation, for example, the parties mustshare information about each firm’s input into thealliance, such as the amount of human resources,physical assets and financial investments (Sluytset al. 2010). Subsequently, the partnering firms mustshare information regarding the division of respon-sibilities and tasks, in addition to the division ofrevenues and profits (Mascarenhas and Koza 2008).During its post-formation phase, the partners mustshare information about the alliance’s progress and

assess its performance, in addition to assessing theperformance of each partner (Sluyts et al. 2010).Sharing know-how will frequently involve contribut-ing and combining valuable resources and skills fromeach partner, because know-how involves knowledgethat is difficult to imitate by outsiders, such thatcombining this knowledge in an alliance can give thepartners a competitive advantage (Dyer and Singh1998). The articles in this review highlight differ-ences in impact between sharing information andsharing know-how regarding alliance performance.Information sharing increases the efficiency of alli-ances (Adams 2001; Schreiner et al. 2009), becauseit decreases search and transaction costs, the costs ofwriting complex contracts, and monitoring costs(Heimeriks and Schreiner 2010; Sampson 2005;Spralls et al. 2011). Partners that share know-howincrease the alliance’s innovative output, which mayimprove the market value of the partners as a result ofhigher sales from innovative products (Andersonet al. 2011; Boyd and Spekman 2008; Nielsen andNielsen 2009) (E1 in Figure 2).

The superior ability to transfer information andknow-how between partners by firms with generalAMC is described by several studies in this review(A1 in Figure 1). Cui and O’Connor (2012, p. 28)posit, for example, that ‘dedicated functions of alli-ance management help the firm systematically accu-mulate competencies of managing informationexchange and more effectively acquire informationfrom its partners’. Successful firms with AMC thatoperate in a larger network with multiple partnerswill ‘(1) have a knowledge specification and a knowl-edge location capability (i.e. know where what typesof content should be placed within the network), (2)be able to efficiently and effectively gather, synthe-size and distribute key information content to part-ners, (3) be proficient in evaluating the costs andbenefits of various types of information that networkpartners might find commercially valuable, (4) beadept at encouraging partners to share key informa-tion, (5) enhance the ability of partners to receive,process and use information, and (6) know the rightamount of information visibility for the network,which directly facilitates information exchange andincreases communication quality’ (Spralls et al.2011, pp. 62–63). Firms with AMC have superiorcommunication abilities that enable them to enhancepartners’ willingness to disclose information(Schreiner et al. 2009) and appropriate know-how(Anderson et al. 2011; Chang et al. 2008). Argyresand Mayer (2007) and Mayer and Salomon (2006)



General AMC WithinFirm

Information / Knowledge Sharing

Collective Alliance Goals

Shared Understanding

General AMC Within

Alliance




A1: 1, 2, 5, 6, 12, 13, 14, 15, 17, 21, 25, 32, 35, 37, 42, 46, 50, 51, 52, 53, 58, 59, 63, 64, 65, 67, 70, 73, 77, 78, 79, 82, 83, 85, 87. A2: 1, 30, 42, 70, 76, 78, 85. A3: 6, 15, 37, 42, 54, 70, 79, 85. A4: 32, 36, 63. A5: 13, 30, 35, 42, 46, 70, 77, 78.

A2

A3

A4

A5

A1

C1: 42, 51, 67, 79, 80. C2: 40, 80. C3: 42, 79, 80. C4: 42.

C1

C2

C4

C3

Partner-specificAMC Within

Firm



B1: 76 B2: 76

B1

B2

Partner-specificAMC Within

Alliance




D1: 3, 12, 26, 33, 40, 42, 43, 51, 57, 62, 66, 67, 68, 90. D2: 30, 40, 57, 68. D3: 12, 42, 69. D4: 42, 62, 69, 80.

D1 D2

D3D4

Figure 1. Impact of AMC on alliance attributes




Alliance Performance

E1: 1, 3, 5, 6, 12, 16, 20, 21, 23, 25, 28, 30, 31, 33, 42, 43, 44, 45, 46, 51, 54, 57, 65, 66, 67, 70, 75, 76, 79, 80, 85, 87, 90. E2: 3, 20, 21, 23, 26, 28, 30, 33, 45, 54, 55, 57, 69, 80, 85. E3: 1, 3, 20, 23, 27, 42, 46, 55, 61, 69, 76, 80, 85.

E1

E2

E3

Figure 2. Impact of alliance attributes on alliance performance



argue that the ability of firms to design effectivecontracts constitutes a particular type of AMC. Firmswith contracting design capabilities craft better exante contracts that specify the knowledge to beexchanged in the alliance and lay the groundworkto foster good communication between partners(Argyres and Mayer 2007; Mayer and Salomon2006). Schilke and Goerzen (2010) claim that firmswith AMC have the managerial competence toabsorb new knowledge from their R&D partners, andRothaermel and Deeds (2006, p. 437) posit that the‘demands of an alliance on a firm’s alliance manage-ment capability are likely to increase commensu-rately with the levels of tacitness, ambiguity andcomplexity involved in the knowledge exchanged inthe alliance’.

Several articles in this review indicate that thepositive impact of general AMC within a firm oninformation and knowledge sharing between partnersmay subsequently lead to a greater focus on collec-tive goals (A2 in Figure 1). The exchange of infor-mation between partners highlights common goals(Spralls et al. 2011), and an open discussion betweenpartners may support the achievement of these goals(Ritala et al. 2009). Schilke and Goerzen (2010)claim that information sharing is necessary to har-monize the activities of partners, to reconcile theirinterests and to achieve mutual objectives. Sampson(2005) argues that communication also allows firmsto align (potential) changes in their strategies andobjectives. It is believed that reliable and regularcommunication between partners and focused com-munication regarding alliance objectives and criticaltask-related information will improve the perfor-mance of the alliance (De Villiers et al. 2007;Duysters et al. 1999; Kale and Singh 2009) (E1 inFigure 2). Several studies also point to a direct rela-tionship between general AMC within the firm andcollective goals (A5 in Figure 1). Canter andTwombly (2010) posit that one of the tasks of alli-ance managers is to achieve a shared objectivebetween the partners, while Heimeriks and Schreiner(2010) posit that AMC may have a positive impact onpartners committing to a common goal.

The exchange of information between partnersleads not only to a focus on collective objectives, butalso to greater shared partner understanding (A3 inFigure 1). Information sharing between partnersleads to shared understanding about common inter-ests (Ritala et al. 2009) and a mutual understandingof the terms of the alliance relationship (Argyres andMayer 2007). Information sharing builds a mutual

understanding regarding the obligations and engage-ment rules of the partners and develops sharedmental models of how to work together effectively(Schreiner et al. 2009). Spralls et al. (2011, p. 63)argue that information sharing between partnersincreases alliance performance because ‘communi-cation fosters shared understanding between networkpartners; it helps align partners’ interests and values;it allows network partners to work collaborativelytoward a shared understanding of what information isimportant and how best to use it’. Several articles inthis review also address the direct relationshipbetween AMC and a shared understanding (A4 inFigure 1). Hansen et al. (2008) refer to contractualmanagement capabilities as a particular type of AMCand argue that some firms have superior abilities towrite contracts that create shared expectations andmutual understanding regarding the alliance. Thesuccess of an alliance will increase when partnersshare values and create a shared identity and ideol-ogy because a shared understanding of the alliancereduces the likelihood of opportunistic behaviour(Kim et al. 2006) (E2 in Figure 1).

Partner-specific AMC within the firm, allianceattributes and performance

As alliance experience grows, firms learn not only tomanage alliances in general, but also to capturegreater partner-specific knowledge when they allywith repeat partners (Zollo et al. 2002). Severalstudies in this review focus on the experience offirms with repeat partners and address the ability offirms to translate partner-specific experience in alli-ance management skills that are used in allianceswith repeat partners (Duysters et al. 2012; Hoangand Rothaermel 2005; Pangarkar 2004).

Sampson (2005) points to the beneficial impact ofpartner-specific AMC within the firm on informationsharing between partners and on the pursuit of col-lective objectives (B1 and B2 in Figure 1). Partner-specific knowledge improves collaborative benefitsby enabling firms to improve communication withthe repeat partner and to identify effective processesfor exchanging information (Sampson 2005,p. 1012). Partner-specific AMC enable firms to coor-dinate with their repeat partner to align the strategiesof each firm with alliance activities and to worktowards a common strategic goal (Sampson 2005,p. 1009, 1027). The beneficial impact of partner-specific AMC on the pursuit of collective goals isimportant for alliance performance, because partners



frequently value alliance goals differently, whichmight hinder collaboration. A survey has shown thatthe majority of alliance failures are at least partlycaused by shifts in partners’ objectives and expecta-tions (Sampson 2005, p. 1012). Variations in thestrategic direction of partners may be inescapableand negatively affect alliance longevity and itseffective functioning (Dyer et al. 2001; Parkhe 1991,pp. 580–581) (E3 in Figure 2). In this review, severalarticles report that establishing objectives that aremutually embraced by the partners leads to alliancesuccess (e.g. Adams 2001; Pavlovich and Corner2006; Sherwood and Covin 2008; Spralls et al.2011). Heimeriks and Schreiner (2010) argue thatinducing firms to commit to a common objectiveleads to a competitive advantage (E3 in Figure 2).

General AMC within the alliance, allianceattributes and performance

General AMC within the alliance refer to best prac-tices that partners capture, share and store within thealliance, and that they apply to improve performance.These best practices are not partner-specific knowl-edge, but can be applied across a wide range ofalliances. The articles in this review argue that part-ners that capture, share, store and apply generalAMC within their alliance stimulate informationsharing between partners, a shared understanding,and a focus on collective goals (C1, C2, C3, C4 inFigure 1). Examples of alliance structures and pro-cesses that partners apply at the inter-firm level thatmay have this type of beneficial effect include cross-company management teams, joint business plan-ning and joint evaluation sessions, external expertsand inter-firm taskforces and committees (Heimeriksand Schreiner 2010; Parise and Casher 2003;Schreiner et al. 2009; Sherwood and Covin 2008).

In cases where partners need to regularly informeach other of their respective actions or decisions,or they must periodically evaluate the evolvingnature of their interdependence and adapt to it,feedback mechanisms such as joint teams arehelpful to quickly process pertinent information.(Kale and Singh 2009, p. 50)

External experts are an important source of special-ized knowledge and can offer advice, training andcodified tools to partners regarding alliance manage-ment. These experts help to ensure that alliance goalsare set realistically and promote mutuality andshared understanding between partners (Heimeriks

et al. 2009, p. 101). Sherwood and Covin (2008, p.167) argue that inter-firm collaboration teams facili-tate alliance success by increasing the informationflow between partners and by facilitating the estab-lishment of clear and mutually embraced goals.Channels of communication that facilitate theexchange of knowledge also ‘enable alliance partnersto overcome different frames of reference’; thus, theystimulate shared understanding (Sherwood andCovin 2008, p. 168). A shared business vision, ashared understanding of what information is impor-tant and how this information can best be used, andshared methods for problem solving, working con-structively and thinking outside the box have all beenreported to be important for alliance success (DeVilliers 2009; De Villiers et al. 2007; Duysters et al.1999; Ertel 2001; Pavlovich and Corner 2006;Spralls et al. 2011). Hunt et al. (2002, p. 24) defineshared values between partners as ‘beliefs incommon concerning what is important/unimportant,appropriate/inappropriate, and right/wrong’. Part-ners who share values will identify with one anotherand will be more committed to the alliance (Huntet al. 2002) (E2 in Figure 2).

Partner-specific AMC within the alliance, allianceattributes and performance

Studies on AMC also discuss partner-specific capa-bilities that have been developed over time by part-ners that enter into consecutive alliances with thesame partners. In these repeat alliances, partner-specific knowledge is stored in inter-firm routines,structures, processes, and contracts (Hoang andRothaermel 2005; Mayer and Argyres 2004; Zolloet al. 2002). Examples of the structures and pro-cesses include joint teams, partner-specific inter-faces, joint business planning sessions and jointalliance evaluation sessions (Heimeriks et al. 2009;Heimeriks and Schreiner 2010; Hoang andRothaermel 2005; Kale and Singh 2009; Pangarkar2004; Zollo et al. 2002). Mayer and Argyres (2004)describe alliance contracts as repositories of partner-specific knowledge that can serve as a means ofcodifying inter-firm routines. When two firms enterinto an alliance, each firm gradually learns about theother’s operations, internal organization structureand decision-making styles. This knowledge eventu-ally enables them to incorporate contract terms thattake such factors into account and thereby improvesthe performance of repeat alliances (Mayer andArgyres 2004, p. 402, 405).



The articles in this review show that inter-firmroutines and structures facilitate the exchange ofinformation and know-how between partners (D1 inFigure 1). For instance, inter-firm routines canfacilitate the exchange of critical task-related infor-mation between partners, and joint alliance teamscan quickly process information regarding actionsand decisions by partners (e.g. Kale and Singh2009). Inter-firm routines also enhance the abilityof firms to recognize valuable knowledge from aparticular partner and to transfer this knowledgeeffectively across inter-firm boundaries (Dyer andSingh 1998; Hoang and Rothaermel 2005). Partnersin repeat alliances with partner-specific experiencecommunicate more efficiently, because they havelearned how to share information (Zollo et al.2002).

Heimeriks et al. (2009, p. 100) claim that partnersthat share knowledge in joint business planning ses-sions will become more aware of the future directionof the alliance, which will help define collectiveobjectives at an early stage. Al-Laham et al. (2008)argue that repeat partners will have developed rou-tines and procedural structures to facilitate learningfrom the partner and that these routines and struc-tures will enable both firms to accomplish the goalsof the alliance more quickly (D2 in Figure 1). Inother words, they will spend less time setting up thealliance and more time exploiting it, which enablesthe partners to create common benefits more quicklyand to convert common benefits to private benefitsmore rapidly (Al-Laham et al. 2008, p. 350) (E3 inFigure 2).

Information sharing in strategy discussionsbetween partners also facilitates development of ashared purpose (Kohtamäki et al. 2013). Heimeriksand Schreiner (2010, p. 161) argue that joint busi-ness planning and joint evaluation sessions ensurethat there are sufficient opportunities to exchangeinformation between partners and that this informa-tion sharing is important for the development ofmutual understanding. Pavlovich and Corner (2006)demonstrate that a shared mindset or a shared frameof reference is important for success because such amindset allows partners to collectively make senseof the new alliance and its place in the environ-ment. They show how shared frames of referenceare collectively constructed during the alliancelifecycle and how such shared perspectives can onlybe attained by laborious communication (Pavlovichand Corner 2006, p. 189) (D3 in Figure 1).Sherwood and Covin (2008) discuss the direct rela-

tionship between partner-specific AMC within thealliance and a shared understanding between part-ners (D4 in Figure 1). Specialized structures, suchas collaboration teams, inter-firm taskforces andcommittees, facilitate repeated exposure to alliancepartners and therefore mutual understanding regard-ing relevant alliance matters (Sherwood and Covin2008, p. 162).

This literature review has resulted in four catego-ries of AMC that may positively affect alliance attrib-utes. First, firms with general AMC demonstrateimproved information sharing, mutual understandingand the pursuit of collective goals, because thesefirms have developed superior abilities to communi-cate, share knowledge and design alliance contracts.Second, firms with partner-specific AMC have builtup greater knowledge of particular partners and aretherefore better able to share information and pursuecollective goals in repeat alliances with such part-ner(s). Third, partners that store general AMC withinthe alliance improve their relationships by installinginter-firm alliance structures, processes and tools thatare known to have a beneficial impact on the alliancerelationship. Fourth, partners also store partner-specific knowledge within the alliance. These part-ners are better able to share information, achieve ashared understanding and pursue collective goals inrepeat alliances, because they have integratedpartner-specific knowledge in their inter-firm alli-ance structures, processes and tools. This review hasalso shown that information and knowledge sharing,a shared understanding and a focus on collectiveobjectives are important antecedents of alliancesuccess.

Conclusion

The research on alliances in the fields of manage-ment, business and economics is extensive. Reviewsof this literature have addressed a host of topics,including inter-firm attributes of the alliance and themanagement of knowledge in alliances (Jolink andNiesten 2012; Meier 2011). This review goes furtherby focusing on the capabilities to store and applyknowledge regarding alliance management and bymaking two novel contributions to the literature.First, this review structures previous empiricalresearch practices by providing a classification ofproxies that are used to measure AMC. This classi-fication distinguishes four categories: general AMCwithin the firm; partner-specific AMC within the



firm; general AMC within the alliance; and partner-specific AMC within the alliance. The first distinc-tion is consistent with research that studies allianceexperience with different types of partners andpartner-specific experience as two distinct forms ofexperience (Hoang and Rothaermel 2005; Ryall andSampson 2006; Sampson 2005; Zollo et al. 2002).The second distinction is consistent with recentobservations by researchers that capabilities may notonly be stored within the firm, but also retainedoutside a firm’s boundaries (e.g. Lichtenthaler2008).

Second, this review unveils an explanatory mecha-nism – as illustrated by the theoretical conjectures ofthe reviewed articles – for the impact of AMC onperformance by stressing the intermediate impact ofAMC on alliance attributes. It thereby contributes tothe literature on dynamic capabilities, because AMCare perceived to be particular types of dynamic capa-bilities and thus higher-order resources that affect thelower-order resources in the alliance. We show thatthe literature on AMC considers several attributes ofthe alliance as determinants of performance, includ-ing information and knowledge sharing betweenpartners, shared partner understanding and a focuson collective objectives. This review offers insightsabout how the four categories of AMC influencethese alliance attributes and subsequently improveperformance. The review demonstrates that theimpact of general AMC within the firm on allianceattributes can mainly be attributed to the communi-cation and contract design capabilities of firms,whereas the impact of partner-specific AMC onalliance attributes is mainly due to greater partner-specific knowledge embedded in the partners. Alli-ance management capabilities stored within thealliance have a positive effect on alliance attributes,because partners store general and partner-specificknowledge in inter-firm alliance structures, pro-cesses and tools.

Future research suggestions

Based on these contributions to the alliance litera-ture, we are able to offer several suggestions forfuture research on AMC. First, future researchshould endeavour to study the impact of each cat-egory of AMC on alliance attributes more systemati-cally. This review summarizes theoretical claimsfrom the literature regarding the impact of AMC onthe alliance and thereby offers a starting point for

future empirical research. With respect to research ondynamic capabilities in general, Ambrosini andBowman (2009, p. 37) have argued that qualitative,smaller sample studies are likely to be more appro-priate for understanding the subtlety of resourcecreation and regeneration processes. A good exampleof a qualitative case study on alliances that examinescollaborative processes in depth is the study by Davisand Eisenhardt (2011), which shows that alli-ances produce more innovations when partnerscollaboratively alter alliance objectives over time.With respect to AMC, exploratory and qualitativestudies are useful in understanding the complex rela-tionship between AMC and alliance attributes, andthey offer a richer understanding of the mechanismslinking AMC to performance.

Second, the capabilities literature distinguishesdifferent types of dynamic capabilities, such as in thefollowing: ‘some are used to integrate resources,some to reconfigure resources; some are about cre-ating new resources, while others are about sheddingresources’ (Ambrosini and Bowman 2009, p. 35).The literature on AMC defines AMC as dynamiccapabilities, but researchers have not yet clarifiedwhether there are differences between general andpartner-specific capabilities in terms of being moreor less dynamic. Future research may study whethergeneral AMC are more important for integrating andcreating new resources with new partners, whereaspartner-specific AMC are more focused on recon-figuring resources with the same partners in repeatalliances.

Third, future research might also address theimpact of AMC on other attributes of the alliance,such as trust, complementary resources, or opportun-istic behaviour by partners (Bertrand and Meschi2005; Jolink and Niesten 2012). Such an approachmight extend the analysis of alliance attributesbeyond the focus on information and knowledgesharing, a shared understanding and collective objec-tives. In addition, future empirical studies couldmake a stronger case for causal relationshipsbetween AMC and alliance attributes. The literaturerefers to the impact of AMC on alliance attributes,but a reversed causality could also be considered:3

when information-sharing needs are high, partnersmay develop AMC to improve performance. Further-more, future research may go beyond the impact ofAMC on a dyadic relationship and examine theimpact of AMC on information and knowledge

3We thank an anonymous referee for suggesting this point.



sharing between multiple alliances in a firm’salliance portfolio (Sarkar et al. 2009). The study bySpralls et al. (2011) offers a good starting point,because it shows that a firm’s capability to manageinter-firm distribution networks has a positive impacton information exchange and communication qualityin the distribution network. With respect to the inter-nal workings of a firm, the impact of AMC on theinternal resources used in alliances is also worthexamining empirically.

The final research suggestion is related to theobservation that current empirical research on AMCfrequently employs a cross-sectional design, andstudies AMC at a particular point in time. Longitu-dinal research can make a valuable contribution tothe study of the evolution of AMC by highlightinghow firms that implement alliance structures, pro-cesses and tools improve information and knowledgesharing in the alliance and stimulate both a sharedunderstanding and a focus on collective goals overtime.

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pert

s(i

.e.A

MC

)ac

hiev

ea

coll

abor

ativ

em

inds

etan

dal

lian

cesu

cces

s.(Q

L).

12.

Boy

dan

dS

pekm

an20

08A

llia

nce

expe

rien

ceA

llia

nce

dura

tion

;cr

oss-

bord

eran

dho

rizo

ntal

alli

ance

s;al

lian

cepo

rtfo

lio

size

and

com

posi

tion

Pro

cess

:In

ter-

firm

info

rmat

ion

shar

ing

rout

ines

Inte

r-fi

rmco

mpe

tenc

yli

tera

ture

Whe

na

firm

has

AM

C(m

easu

red

byal

lian

cedu

rati

on;

cros

s-bo

rder

,ho

rizo

ntal

alli

ance

s;al

lian

cepo

rtfo

lio

size

and

com

posi

tion

),in

dire

ctti

esha

vea

grea

ter

impa

cton

afi

rm’s

mar

ket

valu

e.(H

part

lysu

ppor

ted)

.13

.C

ante

ran

dTw

ombl

y20

10St

ruct

ure:

Ded

icat

edal

lian

cem

anag

er;

vice

-pre

side

ntof

alli

ance

s;al

lian

cedi

rect

orP

ract

ices

and

tool

sof

alli

ance

man

agem

ent

–A

MC

impr

ove

alli

ance

succ

ess.

(QL

).

14.

Car

sten

set

al.

2008

b–

Soc

ial

ecol

ogy

theo

ry,

orga

niza

tion

alan

dm

anag

emen

tli

tera

ture

Ent

repr

eneu

rial

lead

ers

wit

hA

MC

adop

tin

nova

tion

s.(Q

L).

15.

Cha

nget

al.

2008

cA

llia

nce

expe

rien

ce;

rati

oof

afi

rm’s

mar

ket

valu

eto

its

book

valu

eTo

ol:A

llia

nce

guid

elin

es

Res

ourc

e-ba

sed

and

know

ledg

e-ba

sed

pers

pect

ives

,dy

nam

icca

pabi

lity

,ev

olut

iona

ryec

onom

ics,

orga

niza

tion

alle

arni

ng

AM

C,

defi

ned

asth

ein

tera

ctio

nbe

twee

nal

lian

ceex

peri

ence

and

inte

llec

tual

capi

tal

(rat

ioof

afi

rm’s

mar

ket

valu

eto

its

book

valu

e),

posi

tivel

yim

pact

valu

ecr

eati

onof

alli

ance

s,m

easu

red

asst

ock

pric

ere

spon

ses

toal

lian

cean

noun

cem

ents

.(H

supp

orte

d).

16.

Cho

nko

1999

Stru

ctur

e:A

llia

nce

man

ager

,de

dica

ted

alli

ance

team

Pro

cess

:All

ianc

etr

aini

ngA

llia

nce

lite

ratu

reFi

rms

wit

hA

MC

can

gain

am

arke

tpla

cead

vant

age

and

alli

ance

succ

ess.

(QL

).17

.C

uian

dO

’Con

nor

2012

Stru

ctur

e:D

edic

ated

alli

ance

func

tion

;al

lian

cem

anag

erP

roce

ss:A

llia

nce

sem

inar

san

dw

orks

hops

Tool

:All

ianc

ech

eckl

ists

Org

aniz

atio

nan

dm

arke

ting

theo

ry;

lite

ratu

reon

alli

ance

s,in

nova

tion

and

capa

bili

ties

AM

C(m

easu

red

byal

lian

cefu

ncti

on)

mod

erat

eth

ere

lati

onsh

ipbe

twee

nal

lian

cepo

rtfo

lio

reso

urce

dive

rsit

yan

dfi

rmin

nova

tion

.AM

Cen

able

dive

rsit

yto

posi

tivel

yaf

fect

inno

vati

on.

(Hsu

ppor

ted)

.18

.D

eM

an20

05St

ruct

ure:

VP

ofal

lian

ces;

alli

ance

offi

ce;

alli

ance

spec

iali

st;

alli

ance

man

ager

;ga

teke

eper

Pro

cess

:In

tern

alan

dex

tern

alal

lian

cetr

aini

ng;

part

ner

sele

ctio

npr

oces

s;jo

int

busi

ness

plan

ning

;cu

ltur

epr

ogra

mm

e;pa

rtne

rpr

ogra

mm

e;al

lian

ceev

alua

tion

;jo

int

eval

uati

on;

ince

ntiv

esfo

ral

lian

cem

anag

ers;

mee

ting

sof

alli

ance

man

ager

s;ex

tern

alco

nsul

tant

s;le

gal

expe

rts;

med

iato

rs;

fina

ncia

lex

pert

sTo

ol:A

llia

nce

met

rics

;al

lian

ceda

taba

se

Cap

abil

ity

theo

ryA

MC

are

the

dete

rmin

ants

ofco

mpe

titiv

est

reng

thof

com

pani

esan

dsu

cces

sof

alli

ance

s.A

mer

ican

com

pani

esha

vem

ore

AM

Cth

anE

urop

ean

com

pani

es(H

supp

orte

d).

19.

De

Man

and

Duy

ster

s20

05P

roce

ss:

Cou

rses

and

wor

ksho

pson

alli

ance

man

agem

ent

All

ianc

em

anag

emen

tto

ols

All

ianc

eli

tera

ture

Ahi

gher

leve

lof

AM

Cin

crea

ses

the

inno

vativ

enes

sof

firm

s.(C

).20

.D

eV

illi

ers

etal

.20

07St

ruct

ure:

Ded

icat

edal

lian

cest

aff

All

ianc

eli

tera

ture

AM

Cpo

sitiv

ely

affe

ctal

lian

cesu

cces

s.(H

supp

orte

d).

21.

De

Vil

lier

s20

09St

ruct

ure:

All

ianc

esp

ecia

list

;al

lian

cem

anag

erP

roce

ss:A

llia

nce

trai

ning

;al

lian

ceev

alua

tion

;al

lian

cew

orks

hop

Tool

:All

ianc

eda

taba

se;

alli

ance

chec

klis

t

Man

agem

ent

lite

ratu

reon

alli

ance

sA

MC

posi

tivel

yaf

fect

alli

ance

succ

ess.

(QL

).



App

endi

x1.

Con

tinu

edA

rtic

les

Pro

xies

The

oret

ical

pers

pect

ives

Mai

nar

gum

ent

wit

hre

spec

tto

impa

ctof

AM

Con

perf

orm

ance

d

22.

Dra

ulan

set

al.

2003

cSt

ruct

ure:

All

ianc

esp

ecia

list

sP

roce

ss:T

rain

ing;

indi

vidu

alal

lian

ceev

alua

tion

san

dcr

oss-

alli

ance

eval

uati

ons

Dyn

amic

capa

bili

ties

appr

oach

,re

sour

ce-b

ased

view

,ev

olut

iona

ryec

onom

ics

AM

Cen

hanc

eal

lian

cesu

cces

s(m

easu

red

bym

anag

eria

las

sess

men

tsof

perf

orm

ance

).(H

supp

orte

d).

23.

Duy

ster

set

al.

1999

Stru

ctur

e:A

llia

nce

func

tion

;al

lian

cem

anag

ers

Pro

cess

:All

ianc

etr

aini

ngTo

ol:A

llia

nce

mon

itor

ing;

alli

ance

met

hodo

logy

(one

lang

uage

and

best

prac

tice

s)

All

ianc

eli

tera

ture

AM

Cim

prov

eal

lian

cesu

cces

s.(C

).

24.

Duy

ster

set

al.

2012

Part

ner-

spec

ific

expe

rien

ceSt

ruct

ure:

All

ianc

ede

part

men

t;al

lian

cem

anag

er;

alli

ance

spec

iali

st;

gate

keep

er;

vice

-pre

side

ntof

alli

ance

s;lo

cal

alli

ance

man

ager

Pro

cess

:Fo

rmal

know

ledg

eex

chan

gebe

twee

nal

lian

cem

anag

ers;

appr

oval

proc

esse

s;re

war

dsan

dbo

nuse

sfo

ral

lian

cean

dbu

sine

ssm

anag

ers;

alli

ance

met

rics

;us

eof

own

know

ledg

eab

out

nati

onal

cult

ural

diff

eren

ces;

coun

try-

spec

ific

alli

ance

poli

cies

;ex

tern

alpa

rtie

s:co

nsul

tant

s,fi

nanc

ial

expe

rts,

lega

lex

pert

s,m

edia

tors

for

confl

ict

reso

luti

onTo

ol:A

llia

nce

best

prac

tice

s;da

taba

se;

hand

book

;al

lian

cem

anag

emen

tde

velo

pmen

tpl

an;

trai

ning

inin

terc

ultu

ral

man

agem

ent;

com

pete

ncy

fram

ewor

kfo

ral

lian

cem

anag

ers;

cros

s-al

lian

ceev

alua

tion

;cu

ltur

epr

ogra

mm

e;ex

tern

alan

din

tern

alal

lian

cetr

aini

ng;

indi

vidu

alan

djo

int

alli

ance

eval

uati

on;

intr

anet

;jo

int

busi

ness

plan

ning

;pa

rtne

rpo

rtal

;pa

rtne

rpr

ogra

mm

es;

part

ner

sele

ctio

nap

proa

ch

Org

aniz

atio

nal

lear

ning

theo

ryA

MC

posi

tivel

ym

oder

ate

the

rela

tion

ship

betw

een

alli

ance

port

foli

odi

vers

ity

and

alli

ance

port

foli

ope

rfor

man

ce(m

easu

red

bym

anag

eria

las

sess

men

ts).

AM

Cm

oder

ate

rela

tion

ship

betw

een

dive

rsit

yan

dpe

rfor

man

ceon

lyat

high

leve

lsof

AM

C,

offe

ring

supp

ort

for

the

noti

onth

athi

gher

leve

lsof

dive

rsit

yre

quir

ehi

gher

leve

lsof

AM

C.

(Hsu

ppor

ted)

.

25.

Duy

ster

san

dL

oksh

in20

11b

–A

llia

nce

lite

ratu

reA

llia

nce

port

foli

oco

mpl

exit

yha

san

inve

rse

U-s

hape

dre

lati

onw

ith

inno

vativ

epe

rfor

man

ce.

Lim

its

ofA

MC

are

reac

hed

whe

nin

crea

sing

com

plex

ity

low

ers

perf

orm

ance

.(H

supp

orte

d).

26.

Dye

ran

dS

ingh

1998

Stru

ctur

e:A

llia

nce

func

tion

;di

rect

orof

stra

tegi

cal

lian

ces

Pro

cess

:In

ter-

firm

know

ledg

esh

arin

gro

utin

esTo

ol:

Com

mun

icat

ions

mat

rix;

alli

ance

man

uals

Rel

atio

nal

view

ofco

mpe

titiv

ead

vant

age

AM

Cal

low

firm

sto

gene

rate

rela

tion

alre

nts,

byco

mbi

ning

com

plem

enta

ryre

sour

ces,

shar

ing

know

ledg

e,pa

rtne

ring

wit

hfi

rms

wit

hA

MC

.(C

).



27.

Dye

ret

al.

2001

Stru

ctur

e:D

edic

ated

alli

ance

func

tion

;vi

ce-p

resi

dent

and

dire

ctor

ofal

lian

ces;

alli

ance

man

ager

Pro

cess

:In

tern

alan

dex

tern

altr

aini

ngpr

ogra

mm

es;

inte

rnal

netw

orks

ofal

lian

cem

anag

ers;

proc

esse

sto

shar

ekn

owle

dge;

virt

ual

sum

mit

s;al

lian

cew

orks

hops

Tool

:Val

ue-c

hain

anal

ysis

form

;ne

eds-

anal

ysis

chec

klis

t;m

anuf

actu

ring

-ver

sus-

part

neri

ngan

alys

is;

part

ner

scre

enin

gfo

rm;

tech

nolo

gyan

dpa

tent

-dom

ain

map

s;cu

ltur

al-fi

tev

alua

tion

form

;du

edi

lige

nce

team

;ne

goti

atio

nsm

atri

x;ne

eds-

vers

us-w

ants

chec

klis

t;al

lian

ceco

ntra

ctte

mpl

ate;

alli

ance

-str

uctu

regu

idel

ines

;al

lian

ce-m

etri

csfr

amew

ork;

prob

lem

trac

king

tem

plat

e;tr

ust-

buil

ding

wor

kshe

et;

alli

ance

cont

act

list

;al

lian

ceco

mm

unic

atio

nin

fras

truc

ture

;re

lati

onsh

ipev

alua

tion

form

;ye

arly

stat

usre

port

;te

rmin

atio

nch

eckl

ist;

term

inat

ion-

plan

ning

wor

kshe

et

All

ianc

eli

tera

ture

Firm

sw

ith

AM

Ccr

eate

mor

eal

lian

ceva

lue

and

impr

ove

alli

ance

succ

ess.

(QL

).

28.

Ert

el20

01St

ruct

ure:

All

ianc

em

anag

erP

roce

ss:A

llia

nce

trai

ning

Tool

:All

ianc

em

anua

ls;

tem

plat

es;

alli

ance

heal

thch

ecks

–A

MC

lead

togr

eate

rim

prov

emen

tsin

mar

ket

valu

e.(Q

L).

29.

Faem

set

al.

2010

Stru

ctur

e:D

edic

ated

alli

ance

func

tion

;al

lian

cem

anag

erA

llia

nce

lite

ratu

re,

inno

vati

onli

tera

ture

,re

sour

ce-b

ased

view

All

ianc

epo

rtfo

lio

dive

rsit

yin

crea

ses

shar

eof

pers

onne

lco

sts

inva

lue

adde

d,w

hich

redu

ces

profi

tm

argi

n.(H

supp

orte

d).

Gre

ater

dive

rsit

yim

plie

sin

vest

men

tsin

AM

C,

butA

MC

are

not

mea

sure

d.30

.Fe

ller

etal

.20

13Im

prov

emen

tsin

rele

ase

man

agem

ent,

mil

esto

nes,

allo

cati

onof

task

sSt

ruct

ure:

Ded

icat

edal

lian

cefu

ncti

onP

roce

ss:

Inte

r-or

gani

zati

onal

proc

esse

s;in

ter-

orga

niza

tion

alkn

owle

dge

shar

ing

and

com

mun

icat

ion

rout

ines

Tool

:M

anua

ls,

data

base

s

Kno

wle

dge-

base

dpe

rspe

ctiv

e,ca

pabi

lity

lite

ratu

re

Soc

iali

zati

on,

exte

rnal

izat

ion

and

inte

rnal

izat

ion

ofkn

owle

dge

cont

ribu

teto

deve

lopm

ent

ofA

MC

.(H

supp

orte

d).A

MC

impr

ove

the

deve

lopm

ent

ofne

wpr

oduc

tsan

dpr

oces

ses,

and

are

anim

port

ant

driv

erof

alli

ance

succ

ess.

31.

Fink

and

Kes

sler

2010

All

ianc

eex

peri

ence

Coo

pera

tion

,or

gani

zati

onal

lear

ning

and

evol

utio

nary

theo

ry;

reso

urce

-bas

edvi

ew

AM

Cim

prov

ebu

sine

sspe

rfor

man

ce(m

easu

red

bym

anag

eria

las

sess

men

ts).

(Hpa

rtly

supp

orte

d).

32.

Goe

rzen

2005

Stru

ctur

e:A

ffili

ated

com

pani

esde

part

men

t;re

lati

onsh

ipm

anag

er;

alli

ance

task

forc

eTo

ol:A

llia

nce

guid

elin

es;

alli

ance

wor

ksho

ps

All

ianc

eli

tera

ture

AM

Cre

duce

orga

niza

tion

alco

sts,

enha

nce

com

peti

tive

posi

tion

and

impr

ove

know

ledg

eac

quis

itio

n.(Q

L).

33.

Gru

nwal

dan

dK

iese

r20

07St

ruct

ure:

Ded

icat

edal

lian

cefu

ncti

on;

part

ner-

spec

ific

com

mon

coor

dina

tion

Pro

cess

:All

ianc

etr

aini

ng;

alli

ance

sum

mit

s;st

anda

rdiz

edpr

oced

ures

for

repe

atal

lian

ces

Tool

:All

ianc

egu

idel

ines

,m

anua

ls;

and

tem

plat

es

Org

aniz

atio

nal

lear

ning

theo

ryA

MC

enha

nce

coop

erat

ion

effi

cien

cy,

and

econ

omiz

eon

the

exch

ange

ofco

nten

tkn

owle

dge.

(QL

).



App

endi

x1.

Con

tinu

edA

rtic

les

Pro

xies

The

oret

ical

pers

pect

ives

Mai

nar

gum

ent

wit

hre

spec

tto

impa

ctof

AM

Con

perf

orm

ance

d

34.

Gul

ati

1999

All

ianc

eex

peri

ence

;di

vers

ity

ofal

lian

ceex

peri

ence

;ti

me

dura

tion

sinc

ea

firm

last

ente

red

anal

lian

ceSt

ruct

ure:

All

ianc

eun

its

Tool

:All

ianc

egu

idel

ines

;ch

eckl

ists

;te

mpl

ates

;le

gal

fram

ewor

kfo

ral

lian

ces

Res

ourc

e-ba

sed

view

,ne

twor

kth

eory

,li

tera

ture

onca

pabi

liti

es

The

grea

ter

afi

rm’s

AM

C,

the

grea

ter

the

like

liho

odth

atit

wil

len

ter

ane

wal

lian

cein

the

subs

eque

ntye

ar.

(Hpa

rtly

supp

orte

d,on

lyw

hen

AM

Car

em

easu

red

byex

peri

ence

).

35.

Hag

edoo

rnet

al.

2006

All

ianc

eex

peri

ence

;re

lativ

ebe

twee

nnes

sm

easu

reof

cent

rali

ty;

netw

ork

cons

trai

ntm

easu

reL

iter

atur

eon

lear

ning

and

capa

bili

ties

,ne

twor

kth

eory

The

larg

erth

eA

MC

offi

rms,

the

high

erth

eli

keli

hood

that

firm

sw

ill

enga

gein

futu

real

lian

ceac

tivit

ies.

(Hsu

ppor

ted)

.36

.H

anse

net

al.

2008

Stru

ctur

e:A

llia

nce

func

tion

Cap

abil

itie

sth

eory

,re

sour

ce-b

ased

view

,tr

ansa

ctio

nco

stth

eory

Firm

sw

ith

AM

Cca

nsi

mul

tane

ousl

ypu

rsue

oppo

rtun

ism

min

imiz

atio

nan

dga

inm

axim

izat

ion

obje

ctiv

es.

(C).

37.

Har

tman

net

al.

2010

Stru

ctur

e:P

rocu

rem

ent

depa

rtm

ent;

proc

urem

ent

team

Pro

cess

:Aud

itin

gsy

stem

s;co

nsul

tant

sTo

ol:

Sta

ndar

dize

dco

ntra

cts

Cap

abil

ity

theo

ryA

cqui

siti

on,

deve

lopm

ent

and

appl

icat

ion

ofA

MC

are

esse

ntia

lfo

rth

esu

cces

sful

proc

urem

ent

ofpr

oduc

tsby

publ

icag

enci

es.

(QL

).38

.H

eim

erik

san

dD

uyst

ers

2007

c

Stru

ctur

e:V

ice-

pres

iden

tof

alli

ance

s;al

lian

cede

part

men

t,sp

ecia

list

,m

anag

er;

loca

lal

lian

cem

anag

erP

roce

ss:

Rew

ards

and

bonu

ses

for

alli

ance

man

ager

s;fo

rmal

know

ledg

eex

chan

gebe

twee

nal

lian

cem

anag

ers;

exte

rnal

part

ies:

cons

ulta

nts,

law

yers

,m

edia

tors

,fi

nanc

ial

expe

rts

Tool

:All

ianc

eda

taba

se;

intr

anet

;gu

idel

ines

for

part

ner

sele

ctio

npr

ogra

mm

ean

djo

int

busi

ness

plan

ning

Cap

abil

ity

and

orga

niza

tion

alle

arni

ngth

eory

,re

sour

ce-b

ased

view

,ev

olut

iona

ryec

onom

ics

AM

Car

epo

sitiv

ely

rela

ted

toa

firm

’sal

lian

cepe

rfor

man

ce(m

easu

red

bym

anag

eria

las

sess

men

tsof

perf

orm

ance

).A

MC

med

iate

betw

een

alli

ance

expe

rien

cean

dal

lian

cepe

rfor

man

ce.

(Hsu

ppor

ted)

.

39.

Hei

mer

iks

etal

.20

07c

Stru

ctur

e:A

llia

nce

man

ager

;vi

ce-p

resi

dent

ofal

lian

ces;

alli

ance

depa

rtm

ent;

alli

ance

spec

iali

st;

gate

keep

er;

loca

lal

lian

cem

anag

erP

roce

ss:

Rew

ards

and

bonu

ses

for

alli

ance

man

ager

san

dbu

sine

ssm

anag

ers;

form

ally

stru

ctur

edkn

owle

dge

exch

ange

betw

een

alli

ance

man

ager

s;us

eof

own

know

ledg

eab

out

nati

onal

cult

ural

diff

eren

ces;

alli

ance

met

rics

;co

untr

y-sp

ecifi

cal

lian

cepo

lici

es;

use

ofth

ird

part

ies:

cons

ulta

nts,

law

yers

,fi

nanc

ial

expe

rts,

and

med

iato

rsTo

ol:

Inte

rnal

and

exte

rnal

alli

ance

trai

ning

;tr

aini

ngin

coun

try

diff

eren

ces;

part

ner

sele

ctio

npr

ogra

mm

e;jo

int

busi

ness

plan

ning

;al

lian

ceda

taba

se;

intr

anet

;be

stpr

acti

ces;

cult

ure

and

part

ner

prog

ram

me;

indi

vidu

alan

djo

int

alli

ance

eval

uati

on;

com

pari

son

ofev

alua

tion

s

Cap

abil

ity

and

orga

niza

tion

alle

arni

ngth

eory

,re

sour

ce-b

ased

view

,ev

olut

iona

ryec

onom

ics

All

ianc

eex

peri

ence

and

inte

grat

ing

AM

C(t

rain

ing,

alli

ance

best

prac

tice

s,cu

ltur

epr

ogra

mm

e,al

lian

ceev

alua

tion

and

met

rics

)ar

eke

ydr

iver

sof

alli

ance

succ

ess

(mea

sure

dby

man

ager

ial

asse

ssm

ents

ofpe

rfor

man

ce),

but

not

inst

itut

iona

lizi

ngA

MC

(all

ianc

ede

part

men

tan

dm

anag

er,

vice

-pre

side

ntof

alli

ance

s,pa

rtne

rse

lect

ion

prog

ram

me,

intr

anet

,re

war

ds,

form

alkn

owle

dge

exch

ange

,al

lian

cepo

lici

es).

(Hsu

ppor

ted)

.



40.

Hei

mer

iks

etal

.20

09c

Stru

ctur

e:A

llia

nce

man

ager

;vi

ce-p

resi

dent

ofal

lian

ces;

alli

ance

depa

rtm

ent

Pro

cess

:In

-hou

seco

mpa

nyco

urse

s;in

terc

ultu

ral

trai

ning

prog

ram

mes

;co

urse

sby

exte

rnal

expe

rts,

thir

dpa

rtie

s:co

nsul

tant

s,fi

nanc

ial

expe

rts,

med

iato

rsan

dle

gal

expe

rts

Tool

:G

uide

line

sfo

rpa

rtne

rse

lect

ion

prot

ocol

and

join

tbu

sine

sspl

anni

ng;

codi

fied

best

prac

tice

s;us

eof

best

prac

tice

sfr

omin

divi

dual

alli

ance

sas

inpu

tfo

rne

twor

k-sh

arin

gse

ssio

nsan

din

tran

et

Cap

abil

ity

and

orga

niza

tion

alle

arni

ngth

eory

AM

Cha

vea

posi

tive

impa

cton

alli

ance

port

foli

ope

rfor

man

ce(m

easu

red

bym

anag

eria

las

sess

men

tsof

perf

orm

ance

).A

llia

nce

man

ager

san

dan

intr

anet

are

impo

rtan

tin

help

ing

firm

sm

ove

from

alo

w-p

erfo

rmin

gto

am

ediu

m-p

erfo

rmin

gpo

rtfo

lio,

and

trai

ning

solu

tion

san

dco

difi

edbe

stpr

acti

ces

are

impo

rtan

tin

help

ing

firm

sm

ove

toa

high

-per

form

ing

port

foli

o.(H

supp

orte

d).

41.

Hei

mer

iks

2010

Stru

ctur

e:A

llia

nce

man

ager

;vi

ce-p

resi

dent

ofal

lian

ces;

alli

ance

depa

rtm

ent;

loca

lal

lian

cem

anag

erP

roce

ss:

Rew

ards

alli

ance

man

ager

sti

edto

alli

ance

perf

orm

ance

;fo

rmal

lyst

ruct

ured

know

ledg

eex

chan

gebe

twee

nal

lian

cem

anag

ers;

alli

ance

met

rics

;co

untr

y-sp

ecifi

cal

lian

cepo

lici

esTo

ol:

Inte

rnal

and

exte

rnal

alli

ance

trai

ning

;tr

aini

ngin

coun

try

diff

eren

ces;

part

ner

sele

ctio

npr

ogra

mm

e;in

tran

etto

disp

erse

prac

tice

s;al

lian

cebe

stpr

acti

ces;

cult

ure

prog

ram

me;

com

pari

son

ofal

lian

ceev

alua

tion

sw

ith

part

ner

Cap

abil

ity

and

orga

niza

tion

alle

arni

ngth

eory

Inte

grat

ing

AM

C(t

rain

ing,

alli

ance

best

prac

tice

s,cu

ltur

epr

ogra

mm

e,al

lian

ceev

alua

tion

and

met

rics

)po

sitiv

ely

infl

uenc

eal

lian

cepo

rtfo

lio

perf

orm

ance

(mea

sure

dby

man

ager

ial

asse

ssm

ents

ofpe

rfor

man

ce).

Wit

hin

crea

sing

alli

ance

expe

rien

ce,

inst

itut

iona

lizi

ngA

MC

(all

ianc

ede

part

men

tan

dm

anag

er,

vice

-pre

side

ntof

alli

ance

s,pa

rtne

rse

lect

ion

prog

ram

me,

intr

anet

,re

war

ds,

form

alkn

owle

dge

exch

ange

,al

lian

cepo

lici

es)

nega

tivel

yaf

fect

perf

orm

ance

.(H

supp

orte

d).

42.

Hei

mer

iks

and

Sch

rein

er20

10c

Stru

ctur

e:A

llia

nce

depa

rtm

ent;

alli

ance

func

tion

;vi

ce-p

resi

dent

ofal

lian

ces;

alli

ance

man

ager

;al

lian

cesp

ecia

list

inal

lian

ce;

alli

ance

gate

keep

erP

roce

ss:A

llia

nce

trai

ning

;us

eof

exte

rnal

spec

iali

sts;

join

tbu

sine

sspl

anni

ng;

join

tev

alua

tion

sess

ions

;m

eeti

ngs

inpa

rtne

rpr

ogra

mm

e;m

edia

tor

Tool

s:A

llia

nce

eval

uati

on;

chec

klis

tfo

rpa

rtne

rse

lect

ion

and

mon

itor

ing;

alli

ance

met

rics

;al

lian

cere

war

dan

dbo

nus

syst

ems;

alli

ance

data

base

;sh

ared

intr

anet

Cap

abil

itie

s-an

dco

mpe

tenc

e-ba

sed

view

,tr

ansa

ctio

nco

stan

dag

ency

econ

omic

s,pr

oces

s-or

ient

ed,

trus

tan

dso

cial

embe

dded

ness

pers

pect

ives

Rel

atio

nal

qual

ity

(i.e

.co

mm

itm

ent,

trus

t,in

form

atio

nex

chan

gean

dco

mm

unic

atio

n,co

nflic

t)m

edia

tes

betw

een

AM

Can

dal

lian

cepe

rfor

man

ce.

(C).

43.

Hoa

ngan

dR

otha

erm

el20

05Pa

rtne

r-sp

ecifi

cal

lian

ceex

peri

ence

;ge

nera

lal

lian

ceex

peri

ence

Stru

ctur

e:D

edic

ated

pers

onne

l;al

lian

cem

anag

ers;

dedi

cate

dal

lian

cefu

ncti

onP

roce

ss:

Inte

r-fi

rmkn

owle

dge

shar

ing

rout

ines

;pa

rtne

r-sp

ecifi

cin

terf

aces

Tool

:All

ianc

em

etri

cs,

man

uals

,da

taba

se,

sim

ulat

ions

Org

aniz

atio

nal

lear

ning

theo

ry,

lite

ratu

reon

capa

bili

ties

Gen

eral

AM

C(m

easu

red

byge

nera

lal

lian

ceex

peri

ence

)po

sitiv

ely

affe

ctjo

int

proj

ect

perf

orm

ance

wit

hdi

min

ishi

ngm

argi

nal

retu

rns.

Part

ner-

spec

ific

AM

C(m

easu

red

bypa

rtne

r-sp

ecifi

cal

lian

ceex

peri

ence

)ne

gativ

ely

affe

ctjo

int

proj

ect

perf

orm

ance

.(H

supp

orte

d).

44.

Hof

fman

n20

05c

Stru

ctur

e:D

edic

ated

alli

ance

func

tion

;vi

ce-p

resi

dent

ofal

lian

ces;

rela

tion

ship

man

ager

;al

lian

ceco

ordi

nato

r;al

lian

cesp

onso

r;al

lian

cego

vern

or;

alli

ance

man

ager

;al

lian

cesp

ecia

list

;in

tern

alco

nsul

tant

Tool

:R

evie

ws,

alli

ance

eval

uati

on;

benc

hmar

king

;co

ngre

sses

and

sem

inar

s;ch

eckl

ists

;m

anua

lsan

dpr

oced

ures

;da

taw

areh

ouse

s;jo

bro

tati

on;

intr

anet

;pe

rfor

man

cem

easu

rem

ent;

ince

ntiv

esy

stem

s

Dyn

amic

capa

bili

ties

view

,al

lian

celi

tera

ture

Firm

sw

ith

bett

erin

stru

men

tsfo

rm

ulti

-all

ianc

em

anag

emen

tha

vebe

tter

AM

Can

dar

em

ore

sati

sfied

wit

hth

epe

rfor

man

ceof

thei

ral

lian

cepo

rtfo

lio.

Firm

sw

ith

mul

tipl

eal

lian

ces

and

AM

Cca

nac

hiev

ea

high

erre

turn

onm

anag

emen

t.(H

supp

orte

d).



App

endi

x1.

Con

tinu

edA

rtic

les

Pro

xies

The

oret

ical

pers

pect

ives

Mai

nar

gum

ent

wit

hre

spec

tto

impa

ctof

AM

Con

perf

orm

ance

d

45.

Hun

tet

al.

2002

cA

llia

nce

expe

rien

ce;

alli

ance

man

ager

deve

lopm

ent

capa

bili

ty;

part

ner

vigi

lanc

eca

pabi

lity

Com

pete

nce-

and

reso

urce

-bas

edvi

ew,

reso

urce

adva

ntag

eth

eory

All

ianc

esar

esu

cces

sful

whe

nth

epa

rtne

rsha

vede

velo

ped

AM

C.A

MC

are

posi

tivel

yre

late

dto

idio

sync

rati

can

dco

mpl

emen

tary

reso

urce

s,w

hich

are

also

dete

rmin

ants

ofal

lian

cesu

cces

s.(C

).46

.Ir

elan

det

al.

2002

Ded

icat

edal

lian

cefu

ncti

on;

alli

ance

man

ager

s;al

lian

cem

anag

emen

tro

utin

esT

rans

acti

onco

stec

onom

ics,

soci

alne

twor

kth

eory

,re

sour

ce-b

ased

view

Firm

sw

ith

AM

Ccr

eate

mor

eva

lue,

achi

eve

aco

mpe

titiv

ead

vant

age,

have

ahi

gher

long

-ter

msu

cces

sra

tean

dha

velo

wer

tran

sact

ion

cost

sfo

rm

anag

ing

alli

ance

s.(C

).47

.K

alai

gnan

amet

al.

2007

All

ianc

eex

peri

ence

,pa

rtne

ral

lian

ceex

peri

ence

Pro

cess

:In

ter-

orga

niza

tion

alro

utin

es;

part

ner-

sele

ctio

nro

utin

esTo

ol:

Kno

wle

dge

stor

esfo

rpa

rtne

r-se

lect

ion

and

alli

ance

desi

gn

All

ianc

eli

tera

ture

The

mag

nitu

deof

fina

ncia

lga

ins

(sho

rt-t

erm

chan

ges

insh

areh

olde

rva

lues

afte

ral

lian

cean

noun

cem

ent)

accr

uing

from

afi

rm’s

AM

C(m

easu

red

byex

peri

ence

)is

high

erfo

rsm

alle

rth

anfo

rla

rger

firm

s.A

MC

ofal

lian

cepa

rtne

rs(m

easu

red

bypa

rtne

ral

lian

ceex

peri

ence

)po

sitiv

ely

affe

ctfi

nanc

ial

gain

sof

larg

erfi

rms.

(Hsu

ppor

ted)

.48

.K

ale

etal

.20

01St

ruct

ure:

Cor

pora

teal

lian

ceof

fice

;al

lian

cem

anag

emen

tte

am;

dire

ctor

stra

tegi

cal

lian

ces

and

alli

ance

team

sP

roce

ss:

Deb

riefi

ngal

lian

cem

anag

ers;

foru

ms

and

netw

orks

ofal

lian

cem

anag

ers

tosh

are

alli

ance

know

ledg

e;in

tern

ally

cond

ucte

dal

lian

cetr

aini

ngpr

ogra

mm

esTo

ol:A

llia

nce

man

agem

ent

guid

elin

es;

wor

kshe

ets;

man

uals

;te

mpl

ates

for

part

ner

asse

ssm

ent

and

sele

ctio

n,al

lian

cene

goti

atio

nan

dal

lian

ceco

ntra

cts;

asse

ssm

ent

tool

sto

eval

uate

orga

niza

tion

alan

dte

chno

logi

cal

fit

All

ianc

eli

tera

ture

Afi

rmw

ith

AM

Cha

sa

larg

erpe

rfor

man

cem

easu

red

bybo

thm

anag

eria

las

sess

men

tsan

dst

ock

mar

ket

gain

saf

ter

anal

lian

cean

noun

cem

ent.

(Hsu

ppor

ted)

.

49.

Kal

eet

al.

2002

cSt

ruct

ure:

Ded

icat

edal

lian

cefu

ncti

onP

roce

ss:

Part

ner-

spec

ific

rout

ines

;jo

int

revi

ews

Dyn

amic

capa

bili

ties

,or

gani

zati

onal

lear

ning

,kn

owle

dge-

and

reso

urce

-bas

edvi

ew,

evol

utio

nary

econ

omic

s

Afi

rmw

ith

AM

Cha

sa

larg

erpe

rfor

man

ce(m

easu

red

bybo

thm

anag

eria

las

sess

men

tsan

dst

ock

mar

ket

gain

saf

ter

anal

lian

cean

noun

cem

ent)

.(H

supp

orte

d).



50.

Kal

ean

dS

ingh

2007

cSt

ruct

ure:

Ded

icat

edal

lian

cefu

ncti

onP

roce

ss:

Deb

riefi

ngof

man

ager

sin

volv

edin

alli

ance

s;re

cord

-kee

ping

and

repo

rtin

gon

inci

dent

s,de

cisi

ons,

acti

ons,

prog

ress

and

perf

orm

ance

ofal

lian

ces;

coll

ectiv

ere

view

ofal

lian

ces;

foru

ms;

info

rmal

shar

ing

ofal

lian

cein

form

atio

n;ro

tati

onof

alli

ance

man

ager

s;in

cent

ives

for

man

ager

sto

shar

eal

lian

cein

form

atio

n;in

tern

alan

dex

tern

altr

aini

ng;

alli

ance

com

mit

tees

and

task

forc

es;

inte

r-fi

rmkn

owle

dge

shar

ing

rout

ines

Tool

:D

atab

ase

wit

hfa

ctua

lin

form

atio

non

alli

ance

s;di

rect

ory

orco

ntac

tli

stof

alli

ance

s;ch

eckl

ists

orgu

idel

ines

;m

anua

ls;

logb

ook;

tem

plat

es

Dyn

amic

capa

bili

ties

and

know

ledg

e-ba

sed

view

Afi

rm’s

dedi

cate

dal

lian

cefu

ncti

onan

dit

sal

lian

cele

arni

ngpr

oces

s(i

.e.

afi

rm’s

AM

C)

posi

tivel

yaf

fect

alli

ance

succ

ess

(man

ager

ial

asse

ssm

ents

).T

heal

lian

cele

arni

ngpr

oces

s(a

rtic

ulat

ion,

codi

fica

tion

,sh

arin

gan

din

tern

aliz

atio

nof

alli

ance

man

agem

ent

know

-how

)pa

rtia

llym

edia

tes

the

rela

tion

ship

betw

een

the

alli

ance

func

tion

and

alli

ance

succ

ess.

(Hsu

ppor

ted)

.

51.

Kal

ean

dS

ingh

2009

cA

llia

nce

expe

rien

ceSt

ruct

ure:

Ded

icat

edal

lian

cefu

ncti

on;

alli

ance

man

ager

;al

lian

cere

view

com

mit

tee;

join

tte

ams

ofal

lian

cepa

rtne

rsP

roce

ss:A

llia

nce

trai

ning

;al

lian

ceap

pren

tice

ship

s;fo

rum

sfo

rsh

arin

gof

alli

ance

know

ledg

eTo

ol:V

alue

-cha

inan

alys

isfo

rm;

tool

tode

cide

part

neri

ngne

edan

dfo

rm;

part

ner

scre

enin

gfo

rm;

tech

nolo

gyan

dpa

tent

-dom

ain

map

s;cu

ltur

al-fi

tev

alua

tion

form

;ne

goti

atio

nsm

atri

x;ne

eds-

vers

us-w

ants

chec

klis

t;al

lian

ceco

ntra

ctte

mpl

ate;

alli

ance

-str

uctu

regu

idel

ines

;al

lian

ce-m

etri

csfr

amew

ork;

prob

lem

trac

king

tem

plat

e;tr

ust-

buil

ding

wor

kshe

et;

alli

ance

cont

act

list

;al

lian

ceco

mm

unic

atio

nin

fras

truc

ture

;re

lati

onsh

ipev

alua

tion

form

;ye

arly

stat

usre

port

;te

rmin

atio

nch

eckl

ist;

term

inat

ion-

plan

ning

wor

kshe

et

Dyn

amic

capa

bili

ties

and

know

ledg

e-ba

sed

view

Firm

sw

ith

AM

Cca

nin

crea

seth

eir

over

all

alli

ance

succ

ess

thro

ugh

alli

ance

expe

rien

ce,

bycr

eati

ngan

alli

ance

func

tion

and

esta

blis

hing

alli

ance

lear

ning

proc

esse

s.(C

).

52.

Kau

fman

nan

dS

chw

artz

2009

Res

ourc

es;

rout

ines

;fi

rm’s

degr

eece

ntra

lity

;st

reng

thof

entr

epre

neur

’sne

twor

k;co

nsul

tant

sN

etw

ork

theo

ryA

MC

posi

tivel

yaf

fect

the

degr

eece

ntra

lity

offi

rms

(i.e

.th

edi

rect

cont

ract

ual

cont

acts

afi

rmha

sw

ith

othe

rfi

rms)

.(H

supp

orte

d).

53.

Kha

lid

and

Lar

imo

2012

c

Pro

cess

:In

tra-

firm

know

ledg

esh

arin

g;in

ter-

firm

know

ledg

esh

arin

gro

utin

es;

chan

nels

ofco

mm

unic

atio

nD

ynam

icca

pabi

liti

es,

orga

niza

tion

alle

arni

ngan

dkn

owle

dge-

base

dvi

ew

AM

Cpo

sitiv

ely

affe

ctal

lian

cepe

rfor

man

ce(m

easu

red

bym

anag

eria

las

sess

men

ts).

(Hsu

ppor

ted)

.

54.

Kha

nna

1998

Stru

ctur

e:C

entr

alal

lian

cem

anag

emen

ten

tity

All

ianc

eli

tera

ture

Part

ner-

spec

ific

AM

Cw

ill

lead

toa

high

erle

vel

ofco

mm

onbe

nefi

ts,

and

agr

eate

rlo

ngev

ity

ofth

eal

lian

ce.

(C).

55.

Kim

etal

.20

06Pa

rtne

r-sp

ecifi

cex

peri

ence

;pr

oced

ures

for

inte

r-fi

rmkn

owle

dge

shar

ing

Org

aniz

atio

nal

ecol

ogy

and

netw

ork

theo

ryA

MC

allo

wfi

rms

tore

ach

thei

rgo

als

quic

kly

and

topu

rsue

new

goal

sth

atre

quir

ech

ange

sin

the

firm

s’ne

twor

k.(C

).56

.K

ind

and

Kny

phau

sen-

Auf

seß

2007

c

Stru

ctur

e:D

edic

ated

alli

ance

func

tion

Dyn

amic

capa

bili

ties

pers

pect

ive

AM

Car

eim

port

ant

for

the

com

peti

tive

posi

tion

ofa

firm

.(Q

L).



App

endi

x1.

Con

tinu

edA

rtic

les

Pro

xies

The

oret

ical

pers

pect

ives

Mai

nar

gum

ent

wit

hre

spec

tto

impa

ctof

AM

Con

perf

orm

ance

d

57.

Koh

tam

äki

etal

.20

13P

roce

ss:

Sha

red

stra

tegy

disc

ussi

ons;

proc

ess

deve

lopm

ent

mee

ting

s;re

lati

onsh

ipst

eeri

nggr

oup

mee

ting

sR

elat

iona

lre

sear

ch,

netw

ork

and

tran

sact

ion

cost

theo

ry,

soci

alca

pita

lli

tera

ture

Rel

atio

nal

capi

tal,

whi

chin

dica

tes

qual

ity

ofin

tera

ctio

nbe

twee

nal

lian

cepa

rtne

rs,

has

apo

sitiv

eim

pact

onpr

ofit.

(Hsu

ppor

ted)

.R

elat

iona

lca

pita

lpr

esum

esan

inve

stm

ent

inA

MC

.58

.L

ambe

etal

.20

02c

All

ianc

eex

peri

ence

;al

lian

cem

anag

erde

velo

pmen

tca

pabi

lity

;pa

rtne

rid

enti

fica

tion

prop

ensi

tySt

ruct

ure:

All

ianc

em

anag

er;

dire

ctor

ofst

rate

gic

alli

ance

sP

roce

ss:A

llia

nce

trai

ning

Tool

:All

ianc

eda

taba

se

Res

ourc

e-ba

sed

view

,co

mpe

tenc

e-ba

sed

appr

oach

,re

sour

cead

vant

age

theo

ry

AM

Cco

ntri

bute

toal

lian

cesu

cces

s(m

easu

red

byjo

int

profi

tsof

alli

ance

part

ners

).(H

supp

orte

d).

59.

Lav

ieet

al.

2007

Ext

erna

lin

volv

emen

t:pa

rtic

ipat

ion

innu

mbe

rof

com

peti

ngal

lian

ces

Lit

erat

ure

onca

pabi

liti

es,

alli

ance

lite

ratu

reE

xter

nal

invo

lvem

ent

offi

rms

inal

lian

ces

cont

ribu

tes

tofi

rms’

AM

C,

whi

chhe

lpth

emto

extr

act

alli

ance

bene

fits

(mea

sure

dby

prod

uctiv

ity,

mar

ket

succ

ess

and

expo

sure

).(H

supp

orte

d).

60.

Lee

2011

All

ianc

eex

peri

ence

Lit

erat

ure

onal

lian

ces,

rela

tion

ship

mar

keti

ngan

dne

wpr

oduc

tde

velo

pmen

t

The

alig

nmen

tof

cont

ract

term

sw

ith

know

ledg

ecr

eati

onor

know

ledg

eap

prop

riat

ion

inal

lian

cepo

rtfo

lios

has

apo

sitiv

eim

pact

onne

wpr

oduc

tde

velo

pmen

t.(H

supp

orte

d).A

MC

may

bea

mod

erat

ing

fact

or,

and

redu

ceth

ene

edfo

rfo

rmal

cont

ract

term

s.61

.M

asca

renh

asan

dK

oza

2008

Stru

ctur

e:S

enio

rm

anag

erth

atas

sem

bles

alli

ance

team

;do

min

ant

man

agem

ent

ofth

eal

lian

ceby

one

part

ners

,al

lian

cefu

ncti

on,

vice

-pre

side

ntof

alli

ance

sP

roce

ss:

Com

mun

icat

ion

betw

een

man

ager

sof

each

alli

ance

part

ner

Tool

:M

emor

andu

mof

unde

rsta

ndin

gof

stra

tegi

cpu

rpos

eof

alli

ance

All

ianc

eli

tera

ture

AM

Cim

prov

eal

lian

cepe

rfor

man

ce.

(QL

).

62.

May

eran

dA

rgyr

es20

04P

roce

ss:

Inte

rnal

shar

ing

ofal

lian

cekn

owle

dge;

form

alpr

oces

ses

for

shar

ing

expe

rien

ces;

mee

ting

sof

proj

ect

man

ager

s;sh

arin

gof

stat

usre

port

s;in

ter-

firm

know

ledg

esh

arin

gro

utin

esTo

ol:A

llia

nce

cont

ract

Tra

nsac

tion

cost

econ

omic

san

dor

gani

zati

onal

lear

ning

AM

C,

inpa

rtic

ular

alli

ance

cont

ract

ing

capa

bili

ties

,im

prov

eal

lian

cepe

rfor

man

ce.

(QL

).

63.

May

eran

dS

alom

on20

06A

llia

nce

expe

rien

ceR

esou

rce-

base

dvi

ewan

dtr

ansa

ctio

nco

stec

onom

ics

The

rela

tion

betw

een

hold

-up

and

inte

rnal

gove

rnan

cede

crea

ses

inth

epr

esen

ceof

stro

nggo

vern

ance

capa

bili

ties

.(H

supp

orte

d).

Gov

erna

nce

capa

bili

ties

impr

ove

alli

ance

succ

ess

and

redu

ceco

sts.

64.

Naq

shba

ndi

and

Kau

r20

11c

Stru

ctur

e:D

edic

ated

alli

ance

func

tion

Dyn

amic

capa

bili

ties

theo

ryA

MC

have

apo

sitiv

eim

pact

onal

lian

cesu

cces

s,co

mpe

titiv

ead

vant

age,

inno

vativ

eou

tput

and

flex

ibil

ity

ofth

efi

rm.

(C).



65.

Nie

lsen

and

Nie

lsen

2009

All

ianc

eex

peri

ence

;le

vel

ofkn

ow-h

owin

tech

nolo

gy/p

roce

ssas

sess

men

t,kn

owle

dge/

skil

lsac

quis

itio

n,kn

owle

dge/

skil

lpr

otec

tion

Stru

ctur

e:A

llia

nce

man

ager

sP

roce

ss:

Col

labo

rativ

ekn

owle

dge

man

agem

ent

proc

esse

s

Kno

wle

dge-

base

d,or

gani

zati

onal

lear

ning

,an

dso

cial

capi

tal

pers

pect

ives

,li

tera

ture

onca

pabi

liti

es

AM

Cim

prov

eal

lian

cepe

rfor

man

ce(i

nnov

ativ

eim

prov

emen

tsto

prod

ucts

orpr

oces

ses)

.(H

supp

orte

d).

66.

Pang

arka

r20

04Pa

rtne

r-sp

ecifi

cex

peri

ence

;al

lian

cefo

rmat

ion

and

term

inat

ion

expe

rien

ce;

stab

lero

lede

fini

tion

sfo

rbo

unda

rysp

anne

rs;

coop

erat

ion

rout

ines

Org

aniz

atio

nal

lear

ning

theo

ryA

MC

,in

part

icul

arth

eab

ilit

yto

lear

nfr

omal

lian

cefa

ilur

e,re

duce

the

like

liho

odof

futu

real

lian

cete

rmin

atio

ns.

(Hsu

ppor

ted)

.67

.Pa

rise

and

Cas

her

2003

Stru

ctur

e:A

llia

nce

dire

ctor

;al

lian

cem

anag

er;

alli

ance

team

;al

lian

cepr

ofes

sion

al;

offi

ceof

alli

ance

man

agem

ent

Pro

cess

:All

ianc

e-fo

cuse

dco

mm

unit

ies

ofpr

acti

ce;

educ

atio

nal

wor

ksho

ps;

inte

r-fi

rmkn

owle

dge

shar

ing

rout

ines

betw

een

alli

ance

prof

essi

onal

s;in

ter-

firm

virt

ual

team

room

;w

eb-c

onfe

renc

ing

tech

nolo

gies

Tool

:B

est-

prac

tice

repo

sito

ries

;in

stan

tm

essa

ging

;ex

tran

et;

trai

ning

man

uals

;al

lian

ceda

taba

se;

dire

ctor

yw

ith

cont

act

deta

ils;

repo

sito

ryfo

ral

lian

cedo

cum

ents

All

ianc

eli

tera

ture

AM

C,

inpa

rtic

ular

the

capa

bili

ties

tom

anag

eal

lian

cepo

rtfo

lios

,ha

vea

posi

tive

effe

cton

alli

ance

succ

ess.

(QL

).

68.

Pari

sean

dH

ende

rson

2001

Pro

cess

:C

onte

ntle

arni

ng;

part

ner-

spec

ific

lear

ning

;al

lian

cem

anag

emen

tle

arni

ng;

inte

r-fi

rmkn

owle

dge-

shar

ing

rout

ines

Res

ourc

eex

chan

gem

odel

,re

lati

onal

view

ofth

efi

rm

AM

Cin

flue

nce

the

succ

ess

ofal

lian

ces.

(QL

).

69.

Pavl

ovic

han

dC

orne

r20

06b

–L

iter

atur

eon

soci

alca

pita

l,kn

owle

dge,

entr

epre

neur

ship

Firm

sw

ith

AM

Cha

vem

ore

exte

nsiv

ene

twor

kti

esan

dar

em

ore

like

lyto

deve

lop

new

know

ledg

ein

alli

ance

s.(Q

L).

70.

Rit

ala

etal

.20

09St

ruct

ure:

All

ianc

esp

ecia

list

Pro

cess

:Fo

rum

for

inte

r-fi

rmkn

owle

dge

shar

ing

Evo

luti

onar

yec

onom

ics,

reso

urce

-bas

edvi

ewA

MC

are

aso

urce

ofco

mpe

titiv

ead

vant

age

and

wil

lle

adto

mor

esu

cces

sful

alli

ance

s.(Q

L).

71.

Roc

haG

onça

lves

and

Con

ceic

ao-G

onca

lves

2008

c

Exp

erie

nce

wit

hpr

evio

usal

lian

ces;

man

ager

s’sk

ills

atm

anag

ing

alli

ance

s;pr

oact

ivit

yto

war

dsne

wal

lian

ces

Dyn

amic

capa

bili

ties

view

Apo

sitiv

ere

lati

onex

ists

betw

een

the

port

foli

oof

alli

ance

sof

afi

rm(a

sa

prox

yfo

rth

ede

gree

ofab

unda

nce

ofex

tern

alre

sour

ces)

and

firm

’spe

rfor

man

ceou

tcom

es(p

rofi

tabi

lity

and

sale

s).T

his

rela

tion

ism

oder

ated

byA

MC

.(H

supp

orte

d).

72.

Roc

haG

onça

lves

and

Con

ceic

ao-G

onca

lves

2011

c

Exp

erie

nce

wit

hpr

evio

usal

lian

ces;

man

ager

s’sk

ills

atm

anag

ing

alli

ance

s;pr

oact

ivit

yto

war

dsne

wal

lian

ces

Dyn

amic

capa

bili

ties

view

Apo

sitiv

ere

lati

onex

ists

betw

een

the

port

foli

oof

alli

ance

sof

afi

rm(a

sa

prox

yfo

rth

ede

gree

ofab

unda

nce

ofex

tern

alre

sour

ces)

and

firm

’spe

rfor

man

ceou

tcom

es(p

rofi

tabi

lity

and

sale

s).T

his

rela

tion

ism

oder

ated

byA

MC

.(H

supp

orte

d).

73.

Rot

haer

mel

and

Dee

ds20

06c

Poin

tof

dim

inis

hing

tota

lre

turn

sin

the

rela

tion

ship

betw

een

afi

rm’s

alli

ance

san

dit

sne

wpr

oduc

tde

velo

pmen

tSt

ruct

ure:

Offi

ceof

alli

ance

man

agem

ent;

alli

ance

cham

pion

;al

lian

cele

ader

;al

lian

cem

anag

er;

dedi

cate

dal

lian

cefu

ncti

on;

dedi

cate

dun

itP

roce

ss:A

llia

nce

trai

ning

Tool

:D

iagn

osti

cto

ols;

codi

fied

rout

ines

Dyn

amic

capa

bili

ties

view

AM

Cha

vea

posi

tive

effe

cton

perf

orm

ance

(mea

sure

dby

new

prod

uct

deve

lopm

ent)

.(H

supp

orte

d).

74.

Rot

haer

mel

and

Hes

s20

07c

All

ianc

eex

peri

ence

Dyn

amic

capa

bili

ties

pers

pect

ive

AM

Cpo

sitiv

ely

impa

ctin

nova

tive

outp

ut.

(Hno

tsu

ppor

ted)

.



App

endi

x1.

Con

tinu

edA

rtic

les

Pro

xies

The

oret

ical

pers

pect

ives

Mai

nar

gum

ent

wit

hre

spec

tto

impa

ctof

AM

Con

perf

orm

ance

d

75.

Rya

llan

dS

amps

on20

06Fi

rms’

abil

ity

todr

aft

deta

iled

cont

ract

s;al

lian

ceco

ntra

cts;

part

ner-

spec

ific

and

gene

ral

alli

ance

expe

rien

ceR

elat

iona

lco

ntra

ctin

gli

tera

ture

,or

gani

zati

onal

econ

omic

s

All

ianc

eex

peri

ence

incr

ease

sth

ede

tail

ofal

lian

ceco

ntra

cts.

(Hsu

ppor

ted)

.Thi

ssu

gges

tsth

ata

firm

’sal

lian

ceco

ntra

ctin

gab

ilit

y(i

.e.A

MC

)im

prov

esw

ith

expe

rien

cean

dre

duce

sco

ntra

ctin

gco

sts.

76.

Sam

pson

2005

cA

llia

nce

expe

rien

ce;

alli

ance

man

agem

ent

proc

esse

sSt

ruct

ure:

All

ianc

em

anag

emen

tof

fice

s,di

rect

orof

alli

ance

man

agem

ent,

alli

ance

man

ager

Dyn

amic

capa

bili

ties

view

,le

arni

ngth

eory

All

ianc

eex

peri

ence

has

agr

eate

rim

pact

onpe

rfor

man

cew

hen

alli

ance

sar

ech

arac

teri

zed

bya

grea

ter

com

plex

ity

and

unce

rtai

nty.

(Hsu

ppor

ted)

.Thi

sim

plie

sA

MC

posi

tivel

yaf

fect

perf

orm

ance

.77

.S

arka

ret

al.

2009

cSt

ruct

ure:

All

ianc

efu

ncti

on,

alli

ance

man

agem

ent

depa

rtm

ent,

cent

rali

zed

com

pete

ncy

cent

reP

roce

ss:

Part

neri

ngpr

oact

iven

ess;

rela

tion

algo

vern

ance

;po

rtfo

lio

coor

dina

tion

Tool

:Tem

plat

esan

dm

etri

cs

Res

ourc

e-ba

sed

pers

pect

ive

and

dyna

mic

capa

bili

ties

fram

ewor

k

AM

C(m

easu

red

bypa

rtne

ring

pro-

activ

enes

s,re

lati

onal

gove

rnan

ce,

port

foli

oco

ordi

nati

on)

posi

tivel

yin

flue

nce

alli

ance

port

foli

ope

rfor

man

ce(m

easu

red

bym

anag

eria

las

sess

men

ts).

All

ianc

efu

ncti

onst

reng

then

sth

eef

fect

ofpa

rtne

ring

pro-

activ

enes

san

dre

lati

onal

gove

rnan

ceon

perf

orm

ance

.(H

supp

orte

d).

78.

Sch

ilke

and

Goe

rzen

2010

c

Rou

tine

s:in

ter-

orga

niza

tion

alco

ordi

nati

on,

alli

ance

port

foli

oco

ordi

nati

on,

inte

r-or

gani

zati

onal

lear

ning

,al

lian

cepr

o-ac

tiven

ess,

alli

ance

tran

sfor

mat

ion

All

ianc

eex

peri

ence

Stru

ctur

e:A

llia

nce

stru

ctur

es,

alli

ance

unit

s,al

lian

cesp

ecia

list

s,al

lian

ceco

ordi

nato

r,vi

ce-p

resi

dent

ofal

lian

ces,

alli

ance

depa

rtm

ents

Dyn

amic

capa

bili

ties

pers

pect

ive

Five

type

sof

rout

ines

ofA

MC

have

apo

sitiv

eim

pact

onal

lian

cepe

rfor

man

ce(m

easu

red

bym

anag

eria

las

sess

men

ts),

and

AM

Cm

edia

tes

the

impa

ctof

dedi

cate

dal

lian

cest

ruct

ures

and

alli

ance

expe

rien

ceon

alli

ance

perf

orm

ance

.(H

supp

orte

d).

79.

Sch

rein

eret

al.

2009

cSk

ills

:C

oord

inat

ion,

com

mun

icat

ion,

bond

ing

Stru

ctur

e:A

llia

nce

man

ager

;cr

oss-

com

pany

man

agem

ent

team

Dyn

amic

capa

bili

ties

pers

pect

ive

Coo

rdin

atio

n,co

mm

unic

atio

nan

dbo

ndin

gas

pect

sof

AM

Cha

vea

posi

tive

impa

cton

alli

ance

perf

orm

ance

(mea

sure

dby

man

ager

ial

asse

ssm

ents

).(H

supp

orte

d).

80.

She

rwoo

dan

dC

ovin

2008

All

ianc

eex

peri

ence

Stru

ctur

e:Pa

rtne

rin

terf

ace

mec

hani

sms;

coll

abor

atio

nte

ams;

com

mun

icat

ion

inte

rfac

es;

inte

r-fi

rmta

skfo

rces

and

com

mit

tees

Pro

cess

:In

ter-

firm

know

ledg

e-sh

arin

gro

utin

es

Lea

rnin

gth

eory

AM

Cha

vea

posi

tive

effe

cton

tech

nolo

gica

lkn

owle

dge

acqu

isit

ion.

(Hpa

rtly

supp

orte

d,on

lyw

hen

mea

sure

das

part

ner-

spec

ific

expe

rien

ce,

but

not

whe

nm

easu

red

asge

nera

lal

lian

ceex

peri

ence

orco

llab

orat

ion

team

s).

81.

Sim

onin

1997

All

ianc

eex

peri

ence

Stru

ctur

ean

dpr

oces

s:C

olla

bora

tive

man

agem

ent

know

-how

(inc

ludi

ngst

affi

ngan

dtr

aini

ng);

nego

tiat

ion

know

-how

;pa

rtne

rse

arch

ing

know

-how

;kn

owle

dge

and

skil

lstr

ansf

ers;

exit

ing

skil

ls

Org

aniz

atio

nal

lear

ning

and

capa

bili

ties

pers

pect

ives

,re

sour

ce-b

ased

view

AM

Cha

vea

posi

tive

impa

cton

tang

ible

(pro

fit,

mar

ket

shar

e,co

mpe

titiv

ead

vant

age)

and

inta

ngib

lebe

nefi

ts(l

earn

ing

abou

tco

oper

atio

n,le

arni

ngsk

ills

and

com

pete

nces

held

bypa

rtne

r,le

arni

ngsk

ills

and

com

pete

nces

inde

pend

ent

ofpa

rtne

r).

(Hsu

ppor

ted)

.82

.S

ivak

umar

etal

.20

11A

llia

nce

expe

rien

cean

ddi

vers

ity

ofal

lian

cepa

rtne

rsSt

ruct

ure:

All

ianc

em

anag

emen

tfu

ncti

onR

esou

rce-

base

dan

dkn

owle

dge

base

dvi

ew,

TC

E

AM

Cha

vea

posi

tive

effe

cton

inno

vati

on.

(Hpa

rtly

supp

orte

d,on

lyw

hen

mea

sure

dw

ith

expe

rien

ce).

Div

ersi

tyha

sa

nega

tive

effe

ct.



83.

Slu

yts

etal

.20

10c

Stru

ctur

e:A

llia

nce

man

ager

;al

lian

cesp

onso

r;co

mm

unic

atio

nbe

twee

nun

its

insi

deth

efi

rm;

exte

rnal

spec

iali

sts,

such

asal

lian

cese

arch

bure

aus,

law

yers

,m

edia

tors

,ac

coun

tant

s,m

anag

emen

tco

nsul

tant

sP

roce

ss:

Str

ateg

y,m

anag

emen

t,al

lian

cean

dsk

ill

trai

ning

;tr

aini

ngin

lega

l,fi

nanc

ial,

inte

rcul

tura

lis

sues

,co

nflic

tm

anag

emen

tan

din

com

pete

nce

anal

ysis

Tool

:S

trat

egic

grid

wit

hpr

iori

tyra

nkin

gs;

poli

cyon

alli

ance

stra

tegy

;in

terd

epar

tmen

tal

mee

ting

s;in

tran

et;

alli

ance

data

base

;so

cial

netw

ork

soft

war

e;sc

reen

ing

proc

edur

es;

due

dili

genc

ech

eckl

ists

;pa

rtne

rse

lect

ion

prog

ram

me;

proc

edur

eon

alli

ance

nego

tiat

ion;

paym

ent

and

lega

lpo

lici

es;

fina

ncia

lto

ols;

proj

ect

man

agem

ent;

alli

ance

met

rics

;ch

eckl

ists

for

cros

s,jo

int

and

indi

vidu

alal

lian

ceev

alua

tion

;be

nchm

ark

tech

niqu

es

Dyn

amic

capa

bili

ties

view

,st

rate

gic

and

com

pete

nce-

base

dm

anag

emen

tli

tera

ture

,kn

owle

dge-

base

dvi

ewof

the

firm

,or

gani

zati

onal

lear

ning

theo

ry

AM

Cpo

sitiv

ely

infl

uenc

eal

lian

cesu

cces

s.(C

).

84.

Slu

yts

etal

.20

11St

ruct

ure:

All

ianc

ede

part

men

t,al

lian

cem

anag

erP

roce

ss:

Deb

riefi

ngof

man

ager

s;re

cord

keep

ing

ofin

cide

nts/

deci

sion

sin

alli

ance

s;re

port

ing

onal

lian

cepr

ogre

ss/p

erfo

rman

ce;

foru

ms;

info

rmal

shar

ing

ofal

lian

cein

form

atio

n;ro

tati

onof

man

ager

sal

lian

cetr

aini

ng;

coll

ectiv

ere

view

ofal

lian

ces;

man

agem

ent

ince

ntiv

esto

shar

ein

form

atio

n;in

-hou

sean

dex

tern

alal

lian

cetr

aini

ngTo

ol:

Gui

deli

nes,

man

uals

,te

mpl

ates

;da

taba

sew

ith

fact

ual

alli

ance

info

rmat

ion

Res

ourc

e-ba

sed

view

,be

havi

oura

lth

eory

ofth

efi

rm,

and

capa

bili

ties

-/co

mpe

tenc

e-ba

sed

theo

ry

AM

C,

inpa

rtic

ular

alli

ance

lear

ning

proc

esse

s(c

odifi

cati

onan

dsh

arin

g),

have

apo

sitiv

eim

pact

onal

lian

cepe

rfor

man

ce(m

easu

red

bym

anag

eria

las

sess

men

tsof

perf

orm

ance

).C

odifi

cati

onpa

rtia

llym

edia

tes

the

effe

ctof

the

alli

ance

func

tion

onal

lian

cepe

rfor

man

ce.

(Hsu

ppor

ted)

.

85.

Spr

alls

etal

.20

11c

Inte

r-fi

rmdi

stri

buti

onne

twor

kex

peri

ence

;m

anag

erde

velo

pmen

tan

dpa

rtne

rid

enti

fica

tion

capa

bili

ties

Stru

ctur

e:A

llia

nce

man

ager

Pro

cess

:All

ianc

etr

aini

ng

Dyn

amic

capa

bili

ties

view

,re

sour

ce-b

ased

view

,al

lian

celi

tera

ture

The

abil

ity

ofa

firm

tom

anag

ein

ter-

firm

dist

ribu

tion

netw

orks

has

apo

sitiv

eef

fect

ontr

ust,

info

rmat

ion

exch

ange

and

com

mun

icat

ion

qual

ity

inth

ene

twor

k,w

hich

posi

tivel

yaf

fect

resp

onsi

vene

ss,

fina

ncia

lpe

rfor

man

ce,

effi

cien

cy,

effe

ctiv

enes

san

din

nova

tiven

ess.

(Hsu

ppor

ted)

.86

.S

wam

inat

han

and

Moo

rman

2009

Tre

ndin

firm

’sab

ilit

yto

gene

rate

abno

rmal

retu

rns

from

alli

ance

sov

erti

me

Cap

abil

itie

sth

eory

,ne

twor

kth

eory

,m

arke

ting

lite

ratu

re

AM

Cha

vea

posi

tive

effe

cton

valu

ecr

eati

on(m

easu

red

bya

firm

’sab

norm

alst

ock

retu

rns)

.(H

supp

orte

d).

87.

Wal

ter

etal

.20

08S

kill

sto

mak

eal

lian

ce-r

elat

edde

cisi

ons

Stru

ctur

e:D

edic

ated

alli

ance

man

agem

ent

func

tion

,al

lian

cem

anag

ers

Beh

avio

ural

theo

ryof

the

firm

,in

form

atio

npr

oces

sing

theo

ry,

alli

ance

and

capa

bili

tyli

tera

ture

AM

C,

inpa

rtic

ular

skil

lsto

mak

eal

lian

cede

cisi

ons,

have

apo

sitiv

eim

pact

onal

lian

cepe

rfor

man

ce(m

easu

red

bym

anag

eria

las

sess

men

ts).

(Hsu

ppor

ted)

.



App

endi

x1.

Con

tinu

edA

rtic

les

Pro

xies

The

oret

ical

pers

pect

ives

Mai

nar

gum

ent

wit

hre

spec

tto

impa

ctof

AM

Con

perf

orm

ance

d

88.

Was

smer

2010

cSt

ruct

ure:

Ded

icat

edal

lian

cefu

ncti

onP

roce

ss:A

llia

nce

trai

ning

;al

lian

ceev

alua

tion

;pa

rtne

rpr

ogra

mm

eTo

ol:A

llia

nce

data

base

Dyn

amic

capa

bili

ties

view

,or

gani

zati

onle

arni

ng,

know

ledg

e-ba

sed

view

,ev

olut

iona

ryec

onom

ics

AM

Cle

ads

toa

bett

erpe

rfor

man

ceof

alli

ance

san

dcr

eate

sa

com

peti

tive

adva

ntag

efo

rfi

rms.

(C).

89.

Wit

tman

n20

07St

ruct

ure:

All

ianc

em

anag

er;

dedi

cate

dal

lian

cefu

ncti

onC

apab

ilit

ies

theo

ry,

esca

lati

onth

eory

All

ianc

efa

ilur

eis

mor

eli

kely

whe

nm

anag

ers

choo

seno

tto

allo

cate

reso

urce

sto

crea

teA

MC

.(C

).90

.Z

ollo

etal

.20

02A

llia

nce

expe

rien

ceP

roce

ss:

Inte

r-or

gani

zati

onal

rout

ines

;br

ains

torm

ing

sess

ions

;in

tern

altr

aini

ngTo

ol:A

llia

nce

data

base

;kn

owle

dge

man

agem

ent

tool

s;im

plem

enta

tion

man

uals

;in

tran

et

Cap

abil

itie

sth

eory

,ev

olut

iona

ryec

onom

ics,

orga

niza

tion

alle

arni

ng,

tran

sact

ion

cost

econ

omic

s

AM

Cha

vea

posi

tive

impa

cton

alli

ance

perf

orm

ance

(mea

sure

dby

man

ager

ial

asse

ssm

ents

).(H

part

lysu

ppor

ted,

only

whe

nA

MC

refe

rto

part

ner-

spec

ific

expe

rien

ce,

but

not

toge

nera

lex

peri

ence

).

a.A

rtic

les

eith

erre

fer

toth

ese

prox

ies

orth

eyus

eth

ese

prox

ies

inem

piri

cal

rese

arch

.b.A

rtic

les

that

disc

uss

AM

C,

but

dono

tre

fer

topr

oxie

sfo

rA

MC

.c.A

rtic

les

that

refe

rto

AM

Cas

ady

nam

icca

pabi

lity

oras

ahi

gher

-ord

erre

sour

ce.

d.A

rtic

les

wit

hre

fere

nce

to‘h

ypot

hesi

ssu

ppor

ted

orno

t,or

part

lysu

ppor

ted’

are

quan

tita

tive

stud

ies;

QL

refe

rsto

qual

itat

ive

stud

ies,

incl

udin

gca

sest

udie

s,in

terv

iew

san

dex

ampl

esof

com

pani

esw

ith

AM

C;

Cre

fers

toco

ncep

tual

pape

rsan

d/or

lite

ratu

rere

view

s.



the impact of alliance management capabilities on alliance attributes and performance: a literature...

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