1

Relational Specificity in the Co-production of Outcome-based Contracts in Equipment-

based Service1

Irene C.L. Ng2 Xin Ding 3

March 2011

A Research Manuscript Submitted to Strategic Management Journal

Keywords: Outcome-based contracts, co-production, service, equipment-based, strategic alliance,

alliance management

1 Acknowledgement: This research was financially supported by the Engineering & Physical Science Research Council (UK) and BAE Systems on the Support Service Solutions: Strategy & Transition (S4T) project consortium led by the University of Cambridge. The authors gratefully acknowledge the staff of BAE Systems and MBDA as well as members of the ADAPT IPT, 16th Regiment, ATTAC IPT, MoD and the RAF who have all contributed substantially towards this research.

2 Professor Irene C L Ng is a Professor of Marketing Science at the University of Exeter Business School (U.K.), ESRC/AIM Service Fellow and Research Director of the S4T Grant Consortium, Institute of Manufacturing, University of Cambridge. Contact Information: University of Exeter Business School, Streatham Court, Rennes Drive, Exeter EX4 4PU, United Kingdom Tel: +44 (0) 1392 263250, Fax: +44 (0) 1392 263242, Email: Irene.Ng@exeter.ac.uk

3 Professor Xin Ding is an Assistant Professor of Operations Management and Leadership Supervision at the University of Houston (USA). Contact Information: Information and Logistics Technology Department, University of Houston, Houston, Texas, USA 77024 Tel: +1 714 743 4095 , Email: xding@uh.edu

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Relational Specificity in the Co-production of Outcome-based Contracts in Equipment-

based Service

ABSTRACT

This paper investigates the co-production within a strategic alliance of a firm and its customer

where the firm is tasked to deliver outcomes of equipment. We argue that the strategic alliance

between the firm and its customer must involve three components –the alliance structure, the

management (coordination) and its core value transformations. Integrating literature from

marketing, strategy and operations, and in combination with a qualitative study, we derive eight

constructs of relational specificities in value co-production and its impact on the firm’s contract

performance is investigated through a quantitative survey. Our study provides a more integrated

view of how various theoretical domains overlap in practice and contribute to the understanding

of customer orientation in firm-customer alliance and value co-production.

INTRODUCTION

In the past few decades, firms have been called upon to deliver customer value as a major source

of competitive advantage (Payne and Holt, 2001; Eggert, Ulaga and Schultz, 2006; Liu, Leach

and Bernhardt, 2005; Ulaga and Eggert, 2006). Similarly, value and customer orientation is

echoed amongst the academics in different fields (Cannon and Homburg, 2001; Chase and Apte,

1978; Amit and Zott 2001; Ramirez 1999). Indeed, Ravald and Gronroos (1996) claim that a

firm’s ability to provide superior value is regarded as one of the most successful competitive

strategies in the 1990s.

This paper incorporates marketing and strategy studies of value co-creation and co-production as

well as operations management studies of value transformations into strategic alliance literature

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to investigate the alliance management of the firm and its customer in outcome-based contracts.

We argue that the investigation of a strategic alliance between the firm and its customer must

involve three interacting components – that of the alliance structure, the management

(coordination) and the core value transformations. In this study, we study one such alliance

structure -- that of outcome-based contracts, and examine the core transformation activities in the

management and delivery of such contracts for three equipment manufacturers, and the

implications on the firm’s alliance management capability. With outcome-based contracts such

as Rolls Royce’s “Power-by-the-hour®”, the firm is paid not according to its activities such as

delivering spares or repairs to the customer, but based on the outcome of such activities in the

form of hours of engine in the air. Outcome-based contracting (OBC) poses a challenge to firms,

as delivering outcomes requires effective co-production capability within a strategic alliance

with the firm’s customer. Such a capability is embedded within the firm’s ability to put in place

relational specificities i.e. the specific assets of a firm-customer alliance that embodies the

congruity and alignment of firm-customer resources.

Through a qualitative study, we derive eight constructs of relational specificity for outcome-

based contracts, linking core value transformations with the formal and relational mechanisms

for firm-customer alliances towards outcomes. These eight constructs are then mapped onto a

diverse set of theoretical literature on inter-organizational relationships, and operationalized into

a survey instrument. We then quantitatively investigate their interactions and impact on contract

performance.

Our study showed that the value in OBC equipment-based services is delivered through three

forms of transformation – the transformation of material/equipment, transformation of

information, and transformation of behaviors. Through a qualitative study, we propose the

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relational specificities as the alignments and congruity between the firm and the customer around

such transformations, and the human resource (HR) issues that support that congruity. Based on

the findings from the qualitative study, we examine the relational specificities in terms of co-

production inputs, co-production alignments, co-production intervening factors and contract

performance with Partial Least Square (PLS) analysis. Our analysis reveals that, counter-

intuitively, outcome-based contract performance is dependent on the relational specificities of

behavioral and information alignment rather than on material/equipment process and supply

chain alignment. Our results also show that all three alignments are driven by co-production

inputs including complementary competencies and congruence of expectations, and such

relationships are further mediated by HR constructs of perceived control and empowerment of

individuals co-producing within the alliance.

The study contributes towards the understanding of value co-production and the strategic alliance

between the firm and its customer for outcome-based contracts, an increasingly important

alliance structure for manufacturers. By doing so, we also provide a more integrated view of how

various theoretical domains overlap in practice, and contribute to the understanding of customer

orientation in alliance management and value co-production.

This paper is organized as follows. We first review relevant literature to set the foundation for

this study. We then introduce the research context and the qualitative study. Based on the

findings from the qualitative study, we further propose several hypotheses to be tested in the

following quantitative study. The result of the quantitative study is then reported, followed by

discussions and conclusions.

LITERATURE REVIEW

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The notion of value creation has evolved over time. A few decades ago, the focus was on

creating exchange value, i.e. an offering created within the firm and exchanged with the

customer. Value creation was followed by value ‘destruction’ or ‘consumption’ by the customer

and this idea of value was equated with the price paid for the offering (e.g. Porter, 1980). Over

time and with the onset of complex delivery systems of equipment and activities, the concept of

value evolved to value being ‘in-use’ i.e. jointly created between the customer and the firm for

benefits or outcomes ( Payne, Storbacka and Frow, 2003). This view accentuates value creation

within a relationship i.e. value co-creation where resources (i.e. “people, systems, infrastructures

and information” (Gronroos, 2004) work together through processes to achieve the optimum

benefit for the consumer. The value of the contract, and the relationship with the customer, is

therefore embedded within a complex system of delivery and use (cf. Normann and Ramirez,

1993). The concept of value co-creation also has echoes in previous research in operations and

strategy that have emphasized the role of the customer within a service system such as the

customer contact model (Chase and Apte, 2007; Chase and Tansik, 1983), customer interactions

(Johnson, Manyika and Yee, 2005) and value co-production with the customer (Ramirez, 1999).

Within such thinking, recent marketing researchers have proposed that firms do not really

provide value, but merely value propositions (Vargo and Lusch, 2004, 2008) and it is the

customer that determines value and co-creates it with the firm, upon use. Hence, a firm’s product

offering is merely value unrealized until the customer realizes it through co-creation and gains

the benefit. In addition, customers could also contribute to the firm’s value proposition, such as

users assisting in the design of the iPhone, which scholars have termed as co-production, and

such a co-production could also be of value to the customers. Consequently, co-production is

nested within co-creation (Vargo and Lusch, 2008). The above discussion suggests that both co-

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production and co-creation necessitates a strategic alliance between the firm and its customer. Such

an alliance could be achieved in various forms and theoretical paradigms that explain inter-organizational

relationship formation sits within the strategic alliance domain.

Strategic Alliances

Strategic alliances refer to “inter-firm cooperative arrangements aimed at pursuing mutual

strategic goals” (Judge and Dooley, 2006). Ranging from tightly-coupled joint-ventures to

loosely-formed trade associations, alliance structures have received considerable research

interest, as scholars note that firms need to cooperate with others to achieve competitive

advantage, to penetrate new markets or to acquire new capabilities (Bleeke and Ernst, 1995).

Prior research has examined alliance structure from six theoretical paradigms; transaction cost

economics, resource dependence, strategic choice theory, stakeholder theory, learning theory and

institutional theory (Barringer and Harrison, 2000). Although all six paradigms extol the

importance and benefit of strategic alliances, no single theoretical paradigm adequately captures

the complexity in the management and formation of alliances. (Barringer and Harrison, 2000).

A successful alliance should accomplish two goals. First, it must mitigate the risk of

opportunistic behavior (e.g., the control imperative). Researchers who rely on Transaction Cost

Economics (TCE) propose that opportunism could manifest itself through holding up the other

party’s transaction-specific assets (Williamson, 1985). Such assets can be tangible investments

or intangible specialized knowledge that has limited applicability outside the contract.

Opportunistic behavior could arise through misrepresentation of capabilities or resources,

incongruent expectations or by other deviant behavior not hitherto agreed. Consequently,

opportunism can be avoided by evaluating the values, commitment, and capabilities of partners

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(Das and Teng, 2000), specifying governance forms and contract terms (Poppo and Zenger, 2002,

Luo 2002), and managing the cooperative process (Ring and Van de Ven, 1994).

Second, a successful alliance must be able to cooperate and combine resources of parties in the

most efficient and effective manner (e.g., the cooperation imperative) (Gulati and Singh, 1998;

Nickerson and Zenger, 2004). Conceptual and empirical studies have highlighted the difficulties

of achieving effective coordination, of sharing information with other studies discussing how

cultural differences could be overcome as well as the management of conflict (Das and Teng,

2000; Dyer and Singh, 1998; Reuer, Zollo and Singh, 2002). Coordination is essential in the

pooling of resources, division of labour, and integration of activities – all considered critically

important to the survival of an alliance (Sobrero and Schrader, 1998).

While controlling opportunism and achieving coordination are two key aspects of alliance

success, they often interact when it comes to the two research streams of alliance

(governance) structures and alliance management. Researchers of alliance structures have

investigated a variety of co-operative arrangements including direct investment, joint

ventures, supplier relationships, technology licensing, and technology exchange. Various

ways have been proposed to classify these structures (Alter and Hage, 1993) and some

researchers have differentiated the structures into two categories: equity alliances and non-

equity alliances (Teece, Pisano, and Shuen, 1997). Clearly, the degree of opportunism is

embedded within such alliance structures. Opportunism often results in expensive

negotiation of costs ex ante and monitoring such costs ex post (Hennart, 1988) for a given

structure. Yet, as a consequence of ex post monitoring, alliance structures would also have

an impact on alliance management as well, thereby influencing the coordination aspect of

alliance success. This interaction between the two research streams is evident when Reuer

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and Arino (2007) propose that contractual provisions would vary with different alliance

structures. They felt that “the alliance contract establishes the scope of the collaboration

as well as a division of labor by detailing partners’ individual roles and responsibilities. It

also lays out constraints and obligations external to the alliance proper.”

Indeed, the relationship between alliance structure and alliance management is even more

evident within the legal research domain, where boundaries and mechanisms set by contracts are

increasingly used to regulate social relations. Researchers such as Collins (1999) have proposed

that the two are inseparable, i.e. "the kind of legal regulation of contract which best suits the

interests of business is one which supports the expectations of business in entering transactions...

legal regulation should seek to give priority to the business relation, with secondary attention to

the business deal and to relegate the contract to a peripheral role".

Clearly, the study of alliance management cannot be disassociated from the alliance structure

within which the study aims to investigate. The governance of collaboration, its potential for

self-enforcement and the various inter-organizational routines makes one dependent on the other.

We therefore argue that any study into alliance management must include the alliance structure,

as the interdependency between the two would make a study meaningless if one is to take place

without specifying the other.

Value Co-production

In studying alliance management within a structure, a third interacting component is that of value

co-production. Although the benefits of inter-organizational alliances have long been recognized,

anecdotal and empirical evidence suggest that some firms are better able than others to create

and capture value through their alliances (Kale, Dyer, and Singh, 2002). Researchers who

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subscribe to the resource-based view (RBV) argue that sharing complementary resources among

alliance partners increase the value-creation potential (Das and Teng, 2000). For instance,

developed market firms sought partners with local market knowledge and access to distribution

channels while emerging market firms sought partners that helped them secure financial and

technical resources (Hitt et al. 2000). Although RBV provides a good rationale for choosing

alliance partners, it mainly examines the partner selection process from an economic perspective

(Lin, Yang, and Arya 2009). There is much less understanding of what resources are required

and how they can be better aligned between alliance partners to co-produce value. Clearly, the

nature of value – in terms of what is being transformed and how – is critical to the alliance

between the firm and its customer as it would dictate what resources are complementary.

Operations management categorize organization types according to their key transformation

processes such as ‘material-processing operations’, ‘information-processing operations’, and

‘people-processing operations’ – and literature have discussed the various managerial challenges

which differ across the three archetypes (Morris and Johnston, 1987; Ponsignon, Smart and

Maull, 2007). In co-creating value, a hotel would be transforming the customer as its objective of

ensuring a pleasant experience and a good night’s sleep. Conversely, a news organization such as

CNN would be transforming information, to ensure it is disseminated in an interesting and timely

manner. Finally, an equipment manufacturer would be transforming materials, manufacturing a

tangible product for sale in the market. The alliance between a firm and its customer must

therefore take into account what the core transformations are, so as to achieve value in co-

production with its customer. Alliance structures between the firm and the customer, whether the

firm is contracting on tasks, time or outcomes, would clearly have an impact on such value

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transformations, and in the way the alliance is being managed. Our conceptual argument is

summarized in Figure 1.

Insert Figure 1 here

Within this framework, we now specify our domain of investigation. Our study focuses on

outcome-based contracts as an alliance structure for inter-organizational collaboration between

the firm and its customer, and on the alliance management of such outcome-based contracts,

incorporating its core value transformations.

Alliance Structure and the Strategic Importance of Outcome-based Contracts

Outcome-based contracts between firms and customers are increasingly touted as a strategic

imperative, as modern economy moves towards more complex value delivery systems. The past

century has seen manufacturing as key to wealth creation, but developed nations are gradually

becoming service economies (Ramirez, 1999). Even manufacturing have contributed to growth

in services in the form of training, integration with customers’ capabilities, consultancy and other

services related to the provision of equipment (Ren, 2009). Indeed, for many manufacturers to

remain viable, research has recommended that they diversify into the provision of services,

focusing on meeting the needs of equipment usage instead of merely equipment alone (Neely,

2009; Baines et. al. 2007). Large equipment manufacturers such as IBM, BAE Systems and

Rolls-Royce receive over 50 percent of their revenues from services. This has led to an increased

need to understand the outcomes achieved by the combination of equipment, people and

processes, and the nature of value realized by the customer. Many equipment sales, particularly

for complex equipment such as engines or healthcare equipment are no longer merely a case of

handing over the equipment to customers. They also include service contracts for the

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maintenance, repair and overhaul (MRO) of equipment or professional services supporting the

use and management of such equipment, where the value is co-created and inseparable between

the firm and the customer (Bolton, Lemon and Verhoef, 2008). In such cases, relationships are

embedded in the processes and interactions of service delivery between the customer and the

firm over a length of time. Consequently, the cooperation between the firm and its customer is an

alliance that requires a “mutual and synergistic pooling of resources and capabilities and a

substantial degree of co-mingling between partners in terms of people, systems, skills etc. in

order to attain their objectives through sharing tacit knowledge.” (Madhok and Tallman, 1998).

Alliance structure of OBC. Traditional equipment-based services are service contracts where the

cost of spares could be excluded or included in the price (Van Weele, 2002). The firm could also

provide the customer with a cost-plus contract with detailed cost structures to ascertain

reimbursement with a pre-determined profit percentage (Kim, Cohen, and Netessine, 2007). Of

late, there have been a growing number of contracts that focus on outcomes of equipment rather

than the resources involved in its provision. For example, Rolls-Royce’s service to maintain

engines is remunerated on the basis of how many hours the engine is in the air – a concept

known as ‘power by the hour®’. Such outcome-based contracts focus on achieving required

outcomes rather than meeting a set of prescribed specifications (Bramwell, 2003).

Theoretically, outcome-based contracts have a distinctive alliance structure. First, it aligns the

incentives of both parties towards the outcome. In relationships dominated by protection against

opportunism, such as traditional contracts, firms may be reluctant to make unilateral and

voluntary commitments outside the terms of the contract, preferring to take costly safeguards

instead (Parkhe, 1993). OBC creates a structure of mutual orientation that could mitigate

opportunistic behavior (Kale, Dyer, and Singh 2002). This implies that OBC has an ability to

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elicit desired behaviors arising from the incentives within the contract, thus reducing the cost of

servicing over the longer term for the customer. Current literature suggests that if partners share

ownership of an entity, such as an outcome, and are both ‘mutual hostages’ to the outcome, their

incentive to behave opportunistically is likely to decrease (Teece, Pisano, and Shuen 1997).

Second, OBC puts the risk of delivering outcomes primarily on the firm, and secondarily on the

customer. Bearing a larger proportion of the risk in achieving outcomes provides the firm with an

opportunity to integrate resources for both value creation as well as value realization by the

customer (Madhok and Tallman, 1998), thus allowing the firm an opportunity to earn better rents

through more efficient and effective integration of both parties’ resources (Nooteboom, 1996;

Dyer, 1997). Under these circumstances and in the long term, firms may find it in their interest to

invest in designing more reliable products and more efficient repair and logistics capabilities to

increase profitability. This also echoes Parkhe’s (1993) work which applied game theory on

alliance structures and showed that the pattern of payoff characterizing the cooperation has an

impact on the performance of the alliance. Finally, a firm that is capable of achieving such a

coordination role in OBC acquires superior organizational capability which would allow it to

extract further rents from the market, through more of such contracts. The potential extraction of

future rents from such a capability could incentivize the firm to willingly make commitments

outside the terms of the contract, thus increasing the strength of the mutual orientation, resulting

in OBC being a self-enforcing agreement. Scholars have discussed alliance capability (Anand

and Khanna, 2000) as an important part of the firm’s strategies and a source of competitive

advantage (Dyer and Singh, 1998; Kale, Dyer and Singh, 2002).

A number of equipment-based service contracts are moving towards becoming outcome-based

with hopes of significantly decreasing costs, increasing customer satisfaction and reducing

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financial audits (Kim et al., 2007). Yet, despite this growing interest in OBC from both public

and private sectors, little research has examined fundamental theoretical issues underpinning the

dynamic firm-customer alliance relationship in an outcome-based contract, particularly on what

constitutes the capability to coordinate, cooperate and manage such an alliance.

Alliance management in outcome-based contracts. Transaction cost economics suggest two

ways to achieve cooperation. Formal governance mechanisms compel cooperation by specifying,

contractually, the responsibilities and obligations of all parties (Reuer, Zollo, and Singh 2002).

Complex contracts may outline roles, procedures and penalties for non-compliance and

determine outcomes to be delivered. Such governance arrangements are necessary, usually as

safeguards against dire consequences in the event of a breach (Joskow, 1988). Literature in TCE

have shown that formal mechanisms come with the hazards of asset specificity (i.e. the hold up

problem), measurement difficulty and technological uncertainty (Poppo and Zenger, 2002).

Conversely, cooperation can also be achieved through relational governance. In such cases, inter-

organizational exchanges involve exchanges embedded in social relationships (Macneil, 1978)

which could reduce transaction costs (Dyer and Singh, 1998). Such social relationships are more

fluid in nature and allow for flexibility which facilitates adaptation to environmental changes that

could strengthen cooperation through information sharing and solidarity (Mayer and Teece, 2008)

Recent studies show that formal contracts and relational governance could be complementary.

Some studies have looked into the extent that formal or relational mechanisms can determine

specific outcomes, and it has been proposed that while formal mechanisms can deliver

objectively measurable outputs such as delivery time and quantities, outcomes from the

interaction of individuals between firms such as meetings and emails are not so easily specified

(Poppo and Zenger, 2002, Ryall and Sampson, 2009). Other literature suggest that outcomes are

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achieved from an optimal configuration of formal and relational governance. Hoetker and

Mellewigt (2008) propose that property-based assets lend themselves better to formal mechanism

while knowledge-based assets rely on relational governance mechanisms, further endorsing our

argument that firm-customer alliance management has to account for core activities in achieving

outcomes, even while formal or relational governance mechanisms are being investigated.

The emphasis of outcomes has been very much commended in alliance research (e.g. White and

Lui, 2005). Indeed, one criticism of transaction cost perspective is the lack of credit given to the

benefits from collaboration such as learning, trust development, resource pooling and the

reduction of environmental uncertainty from the trust (e.g. Ring and Van de Ven, 1994). Zajac

and Olsen (1993) suggest that a transaction cost perspective has to incorporate a balanced focus

of benefits and costs from an alliance. Such a value perspective has spawned various literature

(e.g. Ramirez, 1999) arguing for a co-production or co-creation focus in strategic alliance, as

discussed previously. Strategic alliance literature also suggest that alliances are used to pursue

strategic objectives by giving firms access to resources they lack, which is not available in the

market or are unaffordable to acquire (Barney, 1986). In the case of outcome-based contracts,

resources to realize value are certainly contextual and accessible only to the customer at the point

of delivery. Thus, Woodruff and Flint (2006) suggested that customers have an obligation to

assess the contextual nature of resources as part of their capability to co-create value. In doing so,

there is a need to understand the customer’s role in the firm’s processes and systems, and the

firm’s role in the customer’s processes and systems within alliance management. Extending this

logic, this implies that it is not merely about what resources and activities are contributed by

each party but how both are aligned to achieve desirable outcomes. Second, it isn’t merely good

relationships between sales persons and top management of both firms that need to be developed

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but also the appropriate behaviors and relationships between employees of both firms. Finally, if

the delivery of a contract is consultancy, business processing, or equipment-based service, the

processes and systems must be in place to deliver the core activities as well.

Relational Specificity. All this implies that value co-creation and co-production of service

contracts is a combination of processes, behaviors, information and equipment acted upon by

both customer and firm employees in achieving contract outcomes. This is also consistent with

the new service-dominant logic (Vargo and Lusch 2004, 2008) where goods and activities are

combined to achieve value-in-use (outcomes). From an alliance management perspective, it is

therefore difficult to tell when formal mechanisms begin and relational mechanism ends. In

addition, it is commonly acknowledged that there is very little research into how alliances are

managed. As the Barringer and Harrison (2000) states, a majority of interorganizational

relationships fail. (p.396)

Since both control mechanisms and trusting relationships are key influencers to alliance

outcomes (Parkhe, 1993), it is important to understand what actually is the nature of such links,

interactions and connections between firms across all its capabilities (human and otherwise), and

in terms of both formal and relational mechanisms, so that cooperation can be achieved.

In studying alliances between firms, Madhok and Tallman (1998) found that: “such alliances

are frequently prone to failure because the partner firms tend not to recognize ex-ante the

nature and extent of transaction–specific investment that is required in the collaborative

relationship to attain these synergies…..the relationship between organizations is not seen

simply as a governance structure of a hybrid nature but, more importantly, as a unique and

productive resource for value creation and realization. In the search for value through the

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alliance, we demonstrate the importance of transaction-specific investment in what can be

termed relational specificity” (bold ours)

This finding echoes a previous study where the nature of interaction within a relationship is a

critical component of the relationship itself (Madhok, 1995). Yet, relational specificity is not

merely relationships between individuals from both organizations but also between the

organizations’ structures and systems that deliver on the core activities. Previous research has

examined relational and formal mechanisms in generic alliances but as we have argued

previously, results would be inconsistent due to the alliance structures and the core activities

across firms that could potentially confound the results. It is no wonder that there isn’t a current

framework for cooperation within alliance literature (White and Lui, 2005). Even for those who

attempt to provide a framework (e.g. White and Lui, 2005), the research has been about the

characteristics of firms (e.g. diversity), tasks (e.g. complexity) and perceptions of threats, rather

than the links and connections i.e. the nature of the relational specificity, between firms. Studies

into relational mechanisms between firms are also centered around trust and relationships which

are essentially links between individuals of the firms. In delivering core activities of an alliance,

relational specificity would have to involve firm, as well as individual level links.

Given this, we argue that there hasn't been sufficient research into the way constructs of

relational and formal mechanisms interact in alliance management for specific structures such as

outcome-based contracts, and we seek to address this gap. A great number of literature agree that

inter-organizational relationships stress the value created by such alliances, and many studies

have extolled the fact that alliances lead to better firm performances (Deeds and Hill, 1996).

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More concretely, we examine the core transformation activities in the management and delivery

of outcome-based contracts for three equipment manufacturers, and derive eight constructs

linking core transformations with the formal and relational mechanisms for firm-customer

alliances towards outcomes. This provides us with insights into the properties of relational

specificity for outcome-based contracts and we label them as such. The properties of such a

specificity could assist firms investing in more efficient and effective contracts with their

customers. These eight constructs are then mapped onto a diverse set of theoretical foundations

of inter-organizational relationships and operationalized into a survey instrument. We then

quantitatively investigate their interactions and impact on contract performance, also to provide a

more systematic view of how various theoretical streams in marketing, operations and strategy

overlap in practice and contribute to the alliance management and value co-production literature.

Research Context, Design and Administration

This study investigates the delivery of two MRO outcome-based service contracts between two

defence contractors and the UK Ministry of Defence (MoD). The outcomes were the availability

of two types of equipment; a fighter jet and a missile system. The first is the ATTAC4 contract

with BAE Systems, for which the primary outcome is to maintain a defined level of available

mission-ready flying hours across a fleet of some 220 Tornado (fastjet) aircraft. The ATTAC

support service has been a successful5 response to the UK’s imperative to significantly cut the

cost of operational flying for the Tornado aircraft. The contractor is paid and incentivized for

performance against outcome-based key performance indicators. The second contract, MBDA’s

4 ATTAC - Availability Transformation: Tornado Aircraft Contract of £947m with the UK MoD http://www.theengineer.co.uk/news/attac-contract-for-bae-systems/297588.article

5 National Audit Office report 17 July 2007: “Transforming logistics support for fast jets”, http://www.nao.org.uk/publications/0607/transforming_logistics_support.aspx

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ADAPT program, provides partnered support for the British Army’s Rapier mobile air defence

missile system. This collaborative service contract between the MoD and industry led by MBDA,

is managed through a joint project team. The contractor is paid and incentivized for performance

against outcome-based contract performance indicators, for which the primary outcome is to

maintain a defined level of percentage availability of the missile system.

The total value of each contract exceeded USD$400 million per annum and had approximately

1,500 people from both the customer and the supplier firms delivering the contract’s outcomes.

Since the contract is outcome-based, the customer has to commit to being responsible and

abiding by the level of use stipulated in the contract, and the firm is obliged to deliver the

outcome of a set number of flying hours on the fighter jet and a fixed percentage availability

over a certain period of time for the missile system for the agreed usage. While the MRO service

is outsourced, the MoD had a big role in the partnership which is to provide Government

Furnished Materials (GFX) including physical facilities, material, data, IT and manpower to

facilitate the firms in achieving the outcomes.

The delivery of these contracts serves as an exemplar for value co-created and co-produced in an

alliance structure where both parties are focused on achieving outcomes.

Study 1: Qualitative Study - Discovering the Core Value Transformations

A qualitative study was conducted to discover what the customer considers to be the firm’s value

offering. The data was collected in four ways. First, meetings and interviews were held to

provide researchers with an understanding of the service rendered under the defence contracts,

which tend to be riddled with jargon. The explanations of the contracts and the jargon in itself

provided invaluable sets of qualitative data, as employees used their understanding of their world

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to convey their interpretation of the service delivered and the role they (and the customer) played

within the system. Second, further insights were gained from 32 in-depth interviews conducted

over six months with employees from both sides to solicit a deeper understanding of their world

and their role in the social construction of the environment. Third, we also accompanied key

employees in walking around the bases and the sites, observing, taking notes and recording their

audio interactions with one another. Finally, minutes of meetings between the employees of both

sides were collected and analyzed, together with an analysis of presentations, reports and other

text-based documents such as maintenance logs. In analysis, the data was coded and categorized

by three researchers and triangulated through discussion between the three. The coding and

categorization centered on distilling and reducing the data to generic value transformations.

Findings

The research found that in the delivery of outcome-based contracts, value is co-produced with

the customer as a combination of three generic transformations.

The three generic transformations are:

(a) Transform materials and equipment (i.e. manufacturing and production, store, move,

repair, install, discard materials and equipment through supply chain, repairs,

obsolescence management, predictive maintenance etc.)

(b) Transform information (i.e. design, store, move, analyse, change information through

knowledge management, information, communication and technological strategies, data

strategies in equipment management etc.)

(c) Transform people (i.e. train use, change use, build trust through education, influence,

build relationships, change mindsets, achieve mental states etc.)

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Our study found that the firm predominantly designed its processes around the transformation of

materials/equipment, considered to be the primary transformation of equipment-based service.

Indeed, operations literature has usually considered one type of transformation to be dominant

(e.g. Slack, Chambers and Johnston, 2004). However, we found that in outcome-based

equipment service, information and people transformation became crucial in ensuring that

outcomes were achieved. Yet, although both people and information transformations were

delivered by the firm, they were mostly tacitly delivered through the interactions of its

employees and the customer, and through ways that both sides manage individually. Finally, the

three transformations interacted with one another. For example, the transformation of customers’

perceptions and usage of equipment had an impact on the supply chain (material/equipment

transformation) and constantly changed the nature of how information was communicated both

ways (information transformation). Our findings also suggested that the transformations were not

executed by the firm alone, but jointly with the customer.

Our qualitative study also found that contract performance is perceived to be dependent not only

on the core transformations, but how the three transformations were aligned with the customer

processes. Through some of the coded data, we found that the alignments were driven by three

factors; that of congruence of expectations of the firm by both parties, congruence of

expectations of the customer by both parties, and complementary competencies between the

employees of the firm. In addition, two further variables could intervene in the relationship – that

of perceived control and degree of empowerment of the firm’s employees. These serve as the

basis through which we investigate the relational specificity of the alliance. To validate these

qualitative observations, we present the hypotheses development for our quantitative study below.

21

Hypothesis development

Relational specificity within Core Transformations

For the firm to be able to manage an alliance with the customer to co-produce value, we argue

that both customer and firm must invest in specific relational assets that exist both at individual

and organizational levels that would aid co-creation. Such relational specificity is embedded in

eight constructs which we discovered from the qualitative study but which we wish to validate

here. It is important to note that the relational specificities are specific assets based on alignments

or congruity between the firm and the customer resources.

First, customer and firm systems to effect core transformation activities must somehow be

aligned. Alignment would then facilitate a symmetric transfer of resources, information and all

that is necessary to ameliorate problems that may arise from the highly uncertain environmental

factors that impact on co-creation to achieve outcomes. Such an alignment must therefore exist

within the core value transformations.

In the transformation of people, the data suggests an attribute that corresponds with the behavior

of both the firm and the customer. The coded data revealed that both parties discussed ideas of

“building relationships”, “having a good relationship” and “getting along” as essential in their

business partnerships. The data also detected conversations of parties having to behave

“sensibly” and “responsibly” in order for the services to be performed and rendered effectively.

As such, an important property of relational specificity is that both the firm and the customer

understand that their behaviors are aligned to ensure effective and efficient cooperation.

H1: Behavioral alignment is positively related to contract performance

22

The qualitative study also highlighted that interactions at the customer interface (alignment)

between the customer’s value creating processes and the firm’s service delivery processes are

important in managing the alliance. The development of linkages and shared ways of operating

between firms and customers would ensure that both parties work smoothly together; this is

consistent with Kanter (1994). Both partners should work together towards improving processes

and products, showing their commitment to shared benefits (Evans and Jukes, 2000). The

benefits are that the companies can mobilize their resources to increase productivity by

tightening the linkages (Magrath and Hardy, 1994), which would include information transfer

between both parties. Thus, in the context of process alignment between firms and customers,

information alignment is the gathering, moving and storing of information between partners.

H2: Information alignment is positively related to contract performance

According to Guimaraes and Bond (1996), determining set-up details, tooling, scheduling,

maintenance, storage, and replenishment for materials and equipment is a success factor in

equipment-based service. Thus, logistics and the supply chain are particularly relevant and both

the firm and the customer should achieve material/equipment process alignment as a property of

relational specificity, i.e. synchronizing both parties’ processes. Synchronizing would enable the

value creation and transfer process, right from the firm to the end customer, to operate as a

seamless chain along which equipment and physical assets flow (Gunasekaran and Yusuf, 2002).

H3: Material/Equipment alignment is positively related to contract performance

Relational Specificity in the Antecedents to Core Transformation alignments

23

Our qualitative study found “competencies” to be an important relational specificity for co-

creation. The study found broad agreements from both the firm and the customer that employing

the “right people” with the right competencies and appropriate “judgment of environment state”

was crucial to the day-to-day operations of the ATTAC/ADAPT contracts and ultimately in

building the business relationship. Hence, it is important to ensure that the skill sets presented in

the relationship between the firm and the customer complement each other. According to Cox

and Townsend (1997), where the firm competencies are not core or complementary to the

customers’ business processes, a weak relationship of no value exists. Yusuf et al (2004)

proposes that the resource competencies required are often difficult to mobilize and retained by

single companies. It is therefore imperative for companies to cooperate and leverage

complementary competencies for enhanced competitive advantage. Huge firms such as

aerospace companies are now teaming up with different competencies to respond to projects that

are too large for any one firm to manage (Crouse, 1991).

H4: Complementary competency is positively associated with co-production alignments of

behavioral (A), information (B), and material/equipment (C)

The communications among supply chain members may foster inter-organizational learning that

is crucially important to competitive success (Powell, Koput, and Smith-Doerr, 1996). As Paulraj,

Lado, and Chen (2008) state, such open and frequent communications is essential to the

maintenance of value-enhancing relationships as they foster greater understanding of complex

competitive issues related to supply chain success, which in turn may lead to increased

behavioral transparency and reduced information asymmetry (Heide and Miner. 1992; Anderson

and Weitz. 1992). Our study also suggested that clear communications about rights and

24

expectations (e.g., congruence of expectations between firms and customers) helps the value co-

production in MRO service (Woodruff and Flint, 2006). This is consistent with Kambil, Friesen

and Sundaram (1999) who argue that while co-creating value, both partners should be clear

about rights and expectations. Customers need to trust the firms not to misuse the information

provided by them and similarly, firms need to actively manage customer expectations.

Parasuraman, Zeithmal and Berry (1988) also argue that customers evaluate quality by

comparing their expectations with their perceptions of the service performance. Thus, in ensuring

cooperation, the firm’s expectation of customers’ roles is just as important. Both parties have to

be congruent in the expectations of each other’s roles to achieve cooperation within the alliance.

H5: Congruence of expectations of self (the firm) is positively associated with co-production

alignments of behavioral (A), information (B), and material/equipment (C)

H6: Congruence of expectations of other (the customer) is positively associated with co-

production alignments of behavioral (A), information (B), and material/equipment (C)

Relational Specificity in Intervening Behavioral Variables

Parts of our qualitative study found that the link between co-production inputs and co-production

alignments may not be straightforward. Two factors, which we claim to be part of specific

relational assets, seemed to have played an intervention role.

First, perceived control as a psychological construct has emerged from the qualitative coded data

to be an important factor. Indeed, perceived control over job-related activities is a frequently-

used construct in organizational behavior research (Smith et al., 1997). This is because humans

have an essential need to control their work environment, and the desire for control arises

25

because it is associated with positive outcome (White, 1959; Rodin, Rennert, Solomon, 1980).

This is also reflected in the study where the interviews reflected the importance of perceived

control in the day-to-day operations of the contract delivery.

H7: Perceived Control mediates the relationship between co-production inputs and co-

production alignments

In our qualitative study, we also found that empowerment to effect change was a key issue from

both the firm’s and the customer’s perspectives. Both parties appeared to recognize that in order

for effective co-production to take place, there must be willingness and a sense of empowerment

for the individual to identify and effect changes especially with the customer operating in a high

state-dependent context and environmental uncertainty.

Most literature on “empowerment” agree that psychological empowerment in the workplace is

useful for organizations in understanding the quality of their service delivery (Conger and

Kanungo, 1988; Schulz et al., 1995; Spreitzer, 1995).

H8: Empowerment for behavioral change mediates the relationship between co-production

inputs and co-production alignments

Study 2: Quantitative Study – Testing the Relationship between Co-production inputs, Co-

production alignments and Contract performance

The relationships between the above theoretical variables of relational specificity are represented

in Figure 2. We suggest that the set of inputs (complementary competency, congruence of

expectations of self (the firm), and congruence of expectations of other (the customer) influence

co-production alignments at behavioral, information, and material/equipment levels, which in

26

turn influence contract performance. The expected causal relationship between inputs and

alignments may also be mediated by the intervening variables of perceived control and

empowerment. All the hypothesized directions of causal relationships are assumed to be positive

in this study.

<Insert Figure 2 here>

Research Methodology

In conducting the quantitative study, we operationalized the constructs into perceptual measures

i.e. the constructs of which measures were developed were constructs from the perceptions of the

attributes by individuals delivering the contract, as previous research has shown that individual

level relationships drive value (Bolton, Lemon and Verhoef, 2008). We felt this was necessary as

it continued to allow us to take a strategic approach in understanding alliance management. In

case there were gaps in operationalizing and measuring these constructs, we proposed

modification or construction of new scales for the purpose of measuring the constructs. Due to

the adaptations and modifications in items scales, one of our objectives was to perform content

face validity of the items and scales with the experts in this field (Gatignon et al., 2002;

Nunnally and Bernstein, 1994); to achieve this, the items were submitted to five academics and

five industrialists working in the field of service research with expertise in availability-based

contracts. We provided each expert with a detailed definition of each item and asked them to

either accept or reject the premise that each particular item reflected the construct (or attribute).

When a majority of the experts responded that an item did not reflect the construct, we removed

the item. Similarly we included a few items based on the experts’ comments (Gatignon et al.,

2002). Some measures (questions) were worded to be positively slanted while others were

27

negatively worded to reduce the possibility that the respondents would simply agree or disagree

with all the measures without providing adequate attention to reading and comprehending the

questions (Venkatraman, 1989). The measures developed are presented in Table 1.

<Insert Table 1 here>

The measures were entered into a web-based survey and sent to all 1500 individuals managing,

delivering, and supporting outcome-based contracts in 2009. The web-based survey also

prevented users from referring to the responses they had given to earlier questions, to reduce

possible common variance problems that could result in inflated reliability measures (Stanton,

1998). Of the 1500, 116 responses were received for the survey. The elimination of incomplete

responses resulted in 96 usable responses which were then used for further analysis. To ensure

that we captured the ‘web’-like nature of the service and its interactions, we received responses

from across the firm and at all levels from management to support (administrative) to the actual

technical and physical delivery of the service. All respondents have been involved in both

contracts during the years of 2008-2009, with 52% working as professionals and 25% working as

executives. A total of 82.3% of the sample worked on the ATTAC contract, while the rest

worked on the ADAPT contract; 78.5% of the sample were male and 66.7% of the subjects were

between 35 and 54 years old. Also, 65.7% of the subjects had at least some college education,

and 71% reported a household income of between £20,000 and £50,000.

We controlled for demographic features such as age, gender, education, income, marital status,

and race to ensure these variables would not be relevant as factors that influence alliance

management performance and contract outcome. We also controlled for the individual’s degree

of interaction with the customer.

28

Measurement Model Analysis and Testing

We first performed a principal component analysis with direct Oblimin rotation and a

confirmatory factor analysis (CFA) to evaluate our scales (Gerbing and Anderson, 1988). We

followed the two-step approach suggested by Gerbing and Anderson (1988) for our measurement

model construction and eliminated measured variables or latent factors that did not fit well in the

initial CFA model. We then performed a separate CFA for each construct to assess whether any

structural model exhibited an acceptable goodness-of-fit level. As a result, we removed three

measurement items; two for the control construct and one for the empowerment construct that

did not load properly. We then fitted the structural model to the purified measured variables

retained from the first step.

In Table 2, we display the estimates of item loadings and reliability for the investigated

constructs in an unconstrained analysis. To examine the psychometric properties of the

measurement model, we analyzed the indicators and constructs for reliability, convergent

validity, and discriminant validity. Each investigated construct provides a Cronbach’s alpha

value and composite reliability greater than .7, in support of the satisfactory reliability of our

scales (Fornell and Larker, 1981; Nunnally, 1978). We assessed the convergent validity of our

scales at both item and construct levels by examining the item loadings and average variance

extracted (AVE) (Fornell and Larker, 1981). An individual item loading greater than .7 suggests

an indicator shares more variance with the construct it measures than with error variances (Gefen,

Straub and Boudreau, 2000). An AVE greater than .5 manifests a construct that shares more

variance with its indicators than with error variances (Fornell and Larker, 1981). As we show in

Table 2, most items load highly on the constructs they measure with item loadings of .7 or

greater, except for three indicators. Our measurement items also converge properly on their

29

intended constructs. The items exhibit good convergent validity, as suggested by the AVE

greater than .5 for each investigated construct.

< Insert Table 2 Here >

Finally, we examined discriminant validity by comparing the correlations among constructs and

the AVE values (Fornell and Larker, 1981). In general, the square root of the AVE for a

construct should be greater than the correlations between that construct and all other constructs.

As shown in Table 3, the square roots of the AVE are greater than any of the corresponding

correlations. Hence, our scales exhibit appropriate discriminant validity. We sought additional

support for discriminant validity by comparing item loadings and cross-loadings in Table 2. All

the items load substantially higher on intended construct than on other constructs, thus further

suggesting our scales possessed adequate discriminant validity (Fornell, 1992).

< Insert Table 3 Here >

Examining Common Method Bias Analysis

Because each respondent answers questions on items pertaining to both independent and

dependent variables, we must assess potential common method bias, though the specificity of the

measurement items and our use of adequate anchors for different scales should reduce this bias.

We first performed Harmon’s single-factor test using exploratory factor analysis to determine if

a single factor emerges or a general factor accounts for the majority of the covariance. Our

results indicate that none of the nine factor accounts for the majority of the variances. We also

examined the common method bias by adding a latent variable that presents common method

(Podsakoff, MacKenzie and Podsakoff, 2003). Our results reveal that when adding a latent

variable that represents common method, model fit improved (χ2 difference = 8.65, df = 492, p

30

< .01) but the variance accounted for by the common method latent variable was only 5.9% of

the total variance. Together, these results suggest that common method bias is not a serious

threat to our analysis (Calson and Perrewe, 1999; Williams, Cote and Buckley, 1989).

Analysis Method

To test the set of hypotheses, we applied the Partial Least Square (PLS) method to investigate the

proposed relationships among co-production inputs, co-production alignments, intervening

variables, and contract performance. Based on component construct concept, PLS is ideally

suited to the early stage of theory building and testing and especially appropriate when the

researcher is primarily concerned with prediction of the dependent variable (Fornell and

Bookstein, 1982). Compared with two-stage least squares, PLS considers all path coefficients

simultaneously and allow direct, indirect, and spurious relationships and estimates the individual

item weightings in the context of the theoretical model rather than in isolation (Birkinshaw,

Morrison and Hulland, 1995). Compared with other multivariate analysis such as LISREL and

Mplus program which are better suited for theory testing, PLS is better suited for explaining

complex relationships (Fornell and Bookstein, 1982). In addition, the PLS procedure has been

gaining interest and has been increasingly used in business research because of its ability to

model latent constructs under conditions of non-normality and small-to-medium sample sizes

(Chin, Marcolin & Newsted, 2003).

The structural equations in PLS are specified as follows:

( ) ξηβξηη ×Γ+×= *,|E

31

( )mηηηηη ,...,, 21= and ( )mξξξξ ,...,, 21= are vectors of unobserved criterion and explanatory

latent variables, respectively. ( )mm×*β is a matrix of coefficient parameters (with zeros in the

diagonal) for η ; and ( )mm×Γ is a matrix of coefficient parameters for ξ .

PLS estimation proceeds in two stages. First, the latent variables are estimated in an iterative

manner by finding successive approximations. The PLS algorithm involves alternations between

the measurement and structural model where parameter estimates in either part of the model are

treated as fixed as the parameters in the other part are estimated. Second, upon convergence, the

measurement and structural relations are estimated by OLS regressions using the latent variables

estimated in the first stage. Alternatively, the latent variables partial least-squares model is

essentially a path analytic model with latent variables.

The PLS estimates and associated p values of the structural model are reported in Table 4. The

sequence of reported results follows the discussion of the model developed earlier and is

represented in Figure 3. The overall fit of the structural model can be evaluated by the incidence

of significant relationships among the constructs on the one hand, and by the explained variance

of the endogenous latent variables on the other. Table 4 shows that several individual

relationships do not pass the .05 significance hurdle. Further, the R squares of behavioral

alignment, information alignment, material and equipment alignment, and contract performance

are .55, .35 .29, and .22 respectively. Given that alignments and contract performance are the

central focuses of the model, it can be concluded that a satisfactory fit is obtained. Empirical

results are reported below. The 'direct' relations among constructs are discussed first. Thereafter,

'mediating' effects will be considered and contrasted with the 'direct' effects.

< Insert Table 4 Here >

32

< Insert Figure 3 Here >

Direct Effect

Alignments and contract performance

It was hypothesized that the alignments between customer and firm systems facilitate a

symmetric transfer of resources, information and all that is necessary to deliver outcomes. The

results in Table 4 and Figure 3 suggest that both behavioral and information alignments provide

significant explanatory power on contract performance, yet the material and equipment

alignment does not have a significant effect on contract performance ( 61β = .40∗∗∗, 62β = .13∗,

63β = .00). Judging from the size of the path-coefficients, one can conclude that in the context of

the outcome-based contract, the direct effect of behavioral alignment and information alignment

are quite important in alliance management to achieve desired outcomes. However, material and

equipment alignment does not have a significant effect on contract performance. Therefore,

while H1 and H2 are supported, H3 is not.

Co-production inputs and alignments

The results from hypotheses H4 through H6 in Table 4 shed light on the relationship between co-

production inputs and alignments. It was hypothesized that co-production inputs serve as a

driver to facilitate co-production alignments. Our data suggests that the complementary skills

and competencies between the firm and customers greatly contribute to symmetric transfer of

resources including behavior ( 11γ = .23***), information ( 21γ = .42***), and materials and

equipment ( 31γ = .39∗∗∗ ) during the co-production of the service. In addition, the positive

relation between congruencies of expectation and co-production alignments add further insights

33

to the question of whether pre-existing expectations drive the alignments in value co-production.

Congruencies of expectations for both self and other positively affect behavioral alignment at

12γ = .32∗∗∗ and 13γ =.34∗∗∗ , respectively. Yet, the congruency of expectation of self has a direct

effect on material and equipment alignment ( 32γ = .14∗) while the congruency of expectation of

other has a direct effect on information alignment ( 23γ = .14∗). Therefore, H4 is supported while

H5 and H6 are partially supported.

Mediating Effect

Perceived control and empowerment as the mediators of co-production alignments

Building on organizational behavior research (Smith et al., 1997; Spreitzer, 1995), we

hypothesize that co-production inputs affect co-production alignments through their effects on

perceived control and empowerment (H7 & H8). The mediation hypotheses require the test of

the following equations: (1) the effects of co-production inputs on co-production alignments; (2)

the combined effects of perceived control and empowerment and co-production inputs on co-

production alignments; and (3) the effects of co-production inputs on perceived control and

empowerment. As suggested by Baron and Kenny (1986), all of these effects must be significant,

but the significance of the associations between co-production inputs and co-production

alignments must be reduced by adding control and empowerment to the model.

The positive effects of co-production inputs on corresponding alignments are shown in Table 5

(Models 1, 3, and 5). The direct effects of co-production inputs on co-production alignments

have been confirmed in H4-H6, which suggest that complementary competencies and

congruency of expectations significantly improve alignments. When control and empowerment

are added into each model for corresponding alignment, the effects of co-production inputs on

34

alignments are reduced. While empowerment is associated with significant improvement of

behavioral alignment (0.22, p < .01) and information alignment (0.13, p < .05), control is

associated with significant improvements of information alignment (0.24, p <.01) and material &

equipment alignment (0.13, p < .05).

< Insert Table 5 Here >

To complete the mediation hypotheses, it is important to show that co-production inputs are

associated with increased levels of control and empowerment for each of the alignment context.

As shown in Table 6, complementary competencies and congruency of expectations are

associated with a higher level of control and empowerment across all three co-production

alignments. To further test the mediation effects, we used the Sobel test or the product-of-

coefficients approach to compute the ratio of ab (a: path coefficient between the independent

variable and the mediator; b: path coefficient between the mediator and the dependent variable)

and its estimated standard error (Sobel, 1986). We computed the p value for this ratio in

reference to the standard normal distribution, and use the significance level to test the hypotheses

of mediation. The Sobel test suggests that empowerment positively and significantly mediates

the relationship between co-production inputs and behavioral alignment at z=2.07, p <.05 level,

while perceived control positively and significantly mediates the relationship between co-

production inputs and information alignment at z = 2.04, p < .05 level. Based on the above tests,

H7 and H8 are partially supported.

< Insert Table 6 Here >

Discussion

35

Our qualitative findings are consistent with the three generic types of transformations in

operations management literature, and we bring these into the strategy literature to argue that

research into value co-production must include alliance structure and management which

incorporate core value transformations. Our results show that in outcome-based equipment

services, value is delivered through all three forms of transformation, through a value

constellation (Normann and Ramirez, 1993), in co-production with the customer. Our

quantitative findings provide an insight into the challenge of managing firm-customer alliances

towards outcomes. Hypotheses 1 and 2 show that contract performance is dependent upon both

behavioral and information alignments. That material and equipment alignment isn’t related to

contractual performance is at first surprising for an equipment-based service but on reflection, is

intuitively plausible since outcome-based equipment essentially puts the entire supply chain and

its installation of parts and equipment into the hands of the firm to deliver the outcome of use of

the equipment by the customer. Thus, alignment of material/equipment processes with the

customer’s processes may not be as relevant to contract performance, even though such

processes may still be crucial to the value proposition. This lends strength to the argument that

alliances structure such as outcome-based contracts interact directly with its management and

core value transformations. Hypothesis 4 shows that complementary competencies drive all co-

production alignments as we have proposed, emphasizing the importance of the complementarity

of resources such as skills, assets and knowledge in co-production. In the case of hypotheses 5

and 6, congruence of expectations drive behavioral alignment but congruency of expectations of

self is not related to information alignment whilst congruency of expectations of other is not

related to material/equipment alignment. The latter point is consistent with the unsupported

hypothesis 3, since if material/equipment alignment is inconsequential to contract performance,

36

expectations of the other by self may then not be deemed to be essential to material/equipment

alignment. With regard to congruency of expectations of the self by the other being unrelated to

information alignment, we can only surmise that sharing of information transcends the

customer’s knowledge of his/her counterpart, throwing light on the heterogeneity of co-

production dynamics.

The mediating effects Hypotheses 7 and 8 add a further level of insight. Control and

empowerment clearly mediate the relationship between all the co-production inputs with

behavioral alignment, which is expected since these variables embody strong HR issues. Yet,

control and empowerment also mediate the relationship between the co-production inputs of

complementary competencies and expectations of self by other. Co-production alignments of

material/equipment and information suggest that for outcome-based contracts, relational issues

have a wider and bigger impact on co-production, affecting operational processes and supply

chains as well. The mediating effects have a further implication. Even if there is complementary

competencies and congruence of expectations between the firm and its customer, a lack of

perceived control and empowerment of employees involved in co-production would result in less

effective co-production alignments, causing lower contract performance. The findings clearly

show the interaction between formal and relational mechanisms in achieving cooperation, as well

as the way such mechanisms are embedded within core value transformations. Our eight

constructs on relational specificity suggest an integrated approach to alliance management for

firm-customer outcomes, as they complement major streams of inter-organizational literature.

These constructs identify the nature of specific relational assets in which firms and customers

invest to achieve successful value co-production and effective contractual performance.

37

Our study contributes to the literature investigating the performance implications of alliance

structure in a few ways. First, it could potentially explain the conflicting findings in the extant

literature on alliance structure and alliance performance, as we show the role of core value

transformations within alliance management as an important element of alliance outcome

success. Second, from a theoretical perspective, we have taken a more systematic approach to

incorporating marketing and operations concepts into strategy literature, achieving a more

concrete specification of customer orientation in the firm’s strategy. The approach offers an

integrative model in which the nature of value co-production constitutes a part of the firm’s

alliance capability. The result is a richer model that can serve as a blueprint for future research

concerning the performance implications of value co-production in firm-customer alliance.

Theoretically, our study contributes to the nature of the relational specificity in firm-customer

strategic alliances. Specifically, we show that relational mechanisms between firms are the

essential links not only between individuals, but between inter-firm systems and processes in

achieving core activities. In doing so, we show how relational and formal mechanisms interact in

the alliance management of outcome-based contracts.

For decision makers, our findings reinforce the need to take a more holistic view of resource

complementarity in strategic alliance management. Other than considering the complementarity

of people, systems and infrastructures, firms should learn customers’ expectations through open

communications. An improved understanding of how customers expect resources to interact can

help firms determine ways to alignment resources efficiently and effectively.

As an empirical study, this paper exhibits several limitations. First, the customer in the chosen

outcome-based contracts is primarily a government body. Such a context may be unique and

38

could limit the external validity which we sacrificed in the interest of internal validity in

understanding the alliance management and co-production of value in outcome-based

equipment-based contracts. Future research could take on other domains under the alliance

structure-management-value transformations framework. A further limitation of our study is that

we chose to investigate two dyads of co-production. Modern supply chains are often multi-

organizational networks with various stakeholders responsible for different components of the

total value offering. Further research should extend the current study towards network co-

production and alignments to achieve core transformations for alliance outcomes.

Conclusion

The study of strategic alliances is often complex and constitute a ‘messy’ problem with several

interacting components across disciplines and functions. Our study provides insights into how

various concepts interact inter-theoretically that is manifested in complex practice. We also

contribute to continuing scholarly work on value co-production and firm-customer strategic

alliances, and shedding light on the complexity of outcome delivery in equipment-based service

settings and the challenge in acquiring such capability for value co-production. Future research

could apply our approach to other complex alliance-based service systems including airports and

healthcare. Our study also suggests the need to apply a trans-disciplinary approach to examine

the range of processes, people and physical assets from stakeholders’ perspectives.

Our study is important for both researchers and practitioners to understand when and why some

alliances could be more effective than others. Particularly for outcome-based contracts where

manufacturers are now called to adopt a sustainability agenda, the capability to manage an

alliance to achieve outcomes could lead to new business models where value is derived from

39

outcomes, rather than manufacturing more equipment. Such a capability could be a strategic

alternative to continuing on the path of producing, consuming and discarding equipment.

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51

Table 1: Construct Measures

Construct Measures on a Likert Scale of 1-5 with 1= strongly disagree and 5 strongly agree

CO-PRODUCTION INPUTS

Complementary Competencies (Sheridan et al 2001, Wong et al 1999, Yusuf et al 2004, Hanna 2007, Zhu et al. 2004, Stratman et al 2002)

Q97. Myself and the personnel I interact with on the customer/company side have complementary skill sets to get the work done Q98. Myself and the personnel I interact with on the customer/company side have complementary roles (i.e. job title and description) to get the work done Q99. Myself and the personnel I interact with on the customer/company side are able to access resources necessary to get the work done Q100. Myself and the personnel I interact with on the customer/company side are able to access the technology necessary to get the work done

Congruence of Expectations of self (Dean et al 2004, Zeithmal et al, 1993, Parasuraman et al 1994, Leventhal 2008)

Q64. I believe the personnel I interact with on the company/customer side knows what I am doing under the contract Q145. I believe the personnel I interact with on the company/customer side knows HOW I am doing the job under the contract Q65. I believe the personnel I interact with on the company/customer side knows what I WILL DO under the contract Q66. I believe the personnel I interact with on the company/customer side knows what I SHOULD DO under the contract Q146. I believe the personnel I interact with on the company/customer side knows HOW I SHOULD DO my job under the contract Q67. I believe the personnel I interact with on the company/customer side knows what I WANT TO DO under the contract

Congruence of Expectations of other (Dean et al 2004, Zeithmal et al, 1993, Parasuraman et al 1994, Leventhal 2008)

Q60. I am clear on what the personnel I interact with on the company/customer side is doing under the contract Q142. I am clear on HOW the personnel I interact with on the company/customer side is doing his/her job under the contract Q61. I am clear on what the personnel I interact with on the company/customer side WILL DO under the contract Q62. I am clear on what the personnel I interact with on the company/customer side SHOULD DO under the contract Q143. I am clear on HOW the personnel I interact with on the company/customer side SHOULD DO his/her job under the contract Q63. I am clear on what the personnel I interact with on the company/customer side WANT TO DO under the contract

CO-PRODUCTION ALIGNMENTS

Information Alignment (Hung et al 2007, Guimaraes et al 1996, Evans et al 2000, Gunasekaran et al 2002, Yusuf et al 2004

Q71. The company's processes of GATHERING information is aligned with the customer's processes to enable the gathering of information Q72. The company’s processes of GIVING information is aligned with the customer’s processes to receive the information Q73. The company’s processes of STORING information is aligned with the customer’s processes to enable the storage of information Q74. The company’s processes of MOVING the information is aligned with the customer’s processes to enable the movement of information

52

Material/Equipment Alignment (Hung et al 2007, Guimaraes et al 1996, Evans et al 2000, Gunasekaran et al 2002, Yusuf et al 2004

Q75. The company’s processes of COLLECTING the material and equipment is aligned with the customer’s processes to enable the collection of material and equipment Q76. The company’s processes of STORING the material and equipment is aligned with the customer’s processes to enable the storage of the material and equipment Q77. The company’s processes of MOVING the material and equipment is aligned with the customer’s processes to enable the movement of the material and equipment Q141. The company’s processes of REPAIRING the material and equipment is aligned with the customer’s processes to enable the movement of the material and equipment Q96. The company’s processes of INSTALLING the material and equipment is aligned with the customer’s processes to enable the installation of the material and equipment

Behavioral Alignment (Leuthesser et al 1995, Reich et al 2000, Reich et al 1996)

Q35. Myself and the personnel I interact with on the customer/company side give each other a clear picture of what goes on behind the scenes in our organization that may impact our work Q36. Myself and the personnel I interact with on the customer/company side give each other ample notice of planned changes that might impact our operations Q37. Myself and the personnel I interact with on the customer/company side do a good job of notifying each other in advance of any schedule changes Q38. Myself and the personnel I interact with on the customer/company side would discuss any plans that might change the nature of the work we are doing Q39. Myself and the personnel I interact with on the customer/company side take the time needed to discuss new ideas Q40. Myself and the personnel I interact with on the customer/company side co-operate in order to APPLY new ideas Q41. Myself and the personnel I interact with on the customer/company side share (reasonable) resources to help in our day to day operations

INTERVENING VARIABLES

Perceived Control (Smith et al 1997, White 1959, Rodin et al 1980, Karsek 1979, Ganster 1989, Dwyer and Ganster 1991)

Q24. I feel that I have control over the decisions that affect my work Q25. I feel that I have control over the VARIETY OF METHODS I employ in completing my work Q26. I feel that I can choose among a VARIETY OF TASKS to do Q27. I feel that I have total control over the quality of the work I'm delivering Q28. I feel that I can dictate how quickly or slowly I have to work Q29. I feel that I am able to decide when to schedule my rest breaks Q32. I feel that I have influence over the policies and procedures of my work unit

Empowerment (Conger et al 1988, Schulz et al 1995, Spreitzer 1995, Thomas et al 1990)

Q48. When interacting with personnel from the customer/company side, I am good at turning problems into opportunities Q49. When interacting with personnel from the customer/company side, I feel I can use my personal judgment to ensure good contract performance Q50. When interacting with personnel from the customer/company side, I feel that my line manager supports me even when I go beyond the normal call of duty Q57. When interacting with personnel from the customer/company side, I feel I can use tactics that would ensure good contract performance Q51. When interacting with personnel from the customer/company side, I feel I can do more than what my job specifies to ensure good contract performance Q52. When interacting with personnel from the customer/company side, I feel I have significant autonomy in that interaction

Contract Performance For the contract you are involved in, how do you think it's going so far? Q16a.The contract is performing well overall Q16b.The contract is doing well on the company side Q16c.The contract is doing well on the customer side

53

Table 2: Item Loadings

Construct SL CR AVE Items

Complementary

Competencies (ξ1) . 81 .61

Myself and the personnel I interact with on the customer/company side have

.78 …… complementary skill sets to get the work done

.74 …… complementary roles to get the work done

.79 …… are able to access resources necessary to get the work done

.81 …… are able to access the technology to get the work done

Congruence of Expectations of self

(ξ2)

.91 .61 I believe the personnel I interact with on the company/customer side

.68 know what I am doing under the contract

.82 …… how I am doing the job under the contract

.78 …… what I will do under the contract

.82 …… what I should do under the contract

.83 …… how I should do my job under the contract

.75 …… what I want to do under the contract

Congruence of Expectations of other

(ξ3)

. 87 .54 I am clear on what the personnel I interact with on the

company/customer side

.78 …… is doing under the contract

.84 …… is doing his/her job under the contract

.83 …… will do under the contract

.63 …… should do under the contract

.67 …… should do his/her job under the contract

.62 …… want to do under the contract

Behavioral

Alignment (η1) . 87 .54

Myself and the personnel I interact with on the customer/company side

.64 …… give each other a clear picture of what goes on behind the scenes in our organization that may impact our work

.75 …… give each other ample notice of planned changes that might impact our operations

.77 …… do a good job of notifying each other in advance of any schedule changes

.63 …… would discuss any plans that might change the nature of the work we are doing

.77 …… take the time needed to discuss new ideas

.81 …… co-operate in order to APPLY new idea

Information

Alignment (η2) .81 .52 The company's processes of

.78 …… gathering information is aligned with the customer's

processes to enable the gathering of information

.76 …… giving information is aligned with the customer’s processes

to receive the information

.61 …… storing information is aligned with the customer’s processes

to enable the storage of information

.73 …… moving the information is aligned with the customer’s

processes to enable the movement of information

54

Table 2: Item Loadings Cont’d

Construct SL CR AVE Items

Material

Alignment (η3) .87 .58

The company's processes of

.85 …… collecting the material &equipment is aligned with the customer’s processes

.76 …… storing the material & equipment is aligned with the customer’s processes

.86 …… moving the material & equipment is aligned with the customer’s processes

.78 …… repairing the material & equipment is aligned with the customer’s processes

.53 …… installing the material & equipment is aligned with the customer’s processes

Perceived Control

(η4) .84 .52 I feel that

.74 …… I have control over the decisions that affect my work

.80

…… I have control over the variety of methods in completing

work

.68 …… I can choose among a variety of tasks to do

.73

…… I have total control over the quality of the work I'm

delivering

.63 …… I can dictate how quickly or slowly I have to work

Empowerment (η5) .83 .52 When interacting with personnel from the customer/company side

.74 …… I am good at turning problems into opportunities

.80

…… I feel I can use personal judgment to ensure contract

performance

.68

…… I feel I can use tactics that would ensure good contract

performance

.73 …… I feel I can do more than job specifies to ensure performance

.63 …… I feel I have significant autonomy in that interaction

Contract

Performance (η6) . 91 .77

For the contract you are involved in, how do you think it's going so far

.87 …… The contract is performing well overall

.90 …… The contract is doing well on the company side

.86 …… The contract is doing well on the customer side

Note: SL = standardized loadings; CR = composite reliability; AVE = average variance extracted. Items are measured on seven-point scales, where 1 represents strongly agree, 4 is the neutral point, and 7 is strongly disagree.

55

Table 3: Des

crip

tive Sta

tistics, R

elia

bility, Corr

elations, and D

iscr

imin

ant Validity

Co

nst

ruct

Co

nst

ruct

M

S.D.

SK

1

2

3

4

5

6

7

8

9

10

1

1

12

1

3

14

1

5

16

1.

Age

5.1

7

0.8

4

1.1

9

1.0

0

2.

Ed

uca

tion

4

.54

3

.10

1

.58

0

.41

1

.00

3.

Gen

der

1

.50

1

.67

1

.06

0

.27

0

.39

1

.00

4.

Inco

me

1.2

9

0.6

0

1.9

4

0.4

5

0.4

8

0.3

4

1.0

0

5.

Mar

ital

3

.44

1

.64

1

.72

0

.34

0

.39

0

.54

0

.36

1

.00

6.

Rac

e 4

.45

1

.75

1

.12

0

.48

0

.53

0

.44

0

.46

0

.61

1

.00

7.

Inte

ract

ion

3

.25

1

.40

1

.13

-0

.18

-0

.15

0

.00

-0

.18

-0

.17

-0

.17

1

.00

8.

Co

mp

lem

enta

ry

co

mp

eten

cies

2

.41

0

.77

0

.34

-0

.11

0

.00

-0

.09

0

.00

-0

.04

-0

.05

0

.24

0.61

9.

Con

gru

ency

of

exp

ecta

tion

of

self

2

.59

0

.71

0

.42

-0

.21

-0

.05

0

.06

-0

.02

-0

.01

-0

.11

0

.41

0.4

2

0.61

10

. C

on

gru

ency

of

exp

ecta

tion

of

oth

ers

2.4

7

0.6

0

0.0

6

-0.1

3

-0.0

5

-0.0

5

-0.0

2

-0.0

8

-0.0

8

0.2

8

0.5

0

0.4

9

0.54

11

. B

ehav

iora

l A

lign

men

t 2

.66

0

.67

0

.44

-0

.19

-0

.09

-0

.03

-0

.06

-0

.05

-0

.15

0

.25

0.5

4

0.5

8

0.6

1

0.54

12

. In

form

atio

n A

lign

men

t 2

.95

0

.60

-0

.19

-0

.10

-0

.05

-0

.15

0

.06

-0

.04

0

.06

0

.10

0.5

0

0.3

1

0.3

7

0.4

3

0.52

13

. M

ater

ial

&

E

qu

ipm

ent

Ali

gn

men

t 2

.65

0

.64

-0

.38

-0

.12

-0

.25

-0

.16

-0

.12

-0

.19

-0

.24

0

.25

0.4

9

0.3

4

0.3

5

0.4

4

0.5

7

0.58

14

. P

erce

ived

Co

ntr

ol

2.6

9

0.7

5

0.5

9

-0.0

2

-0.1

1

0.0

5

-0.0

5

-0.0

3

-0.0

5

0.3

3

0.5

0

0.4

0

0.4

0

0.4

8

0.4

6

0.3

5

0.52

15

. E

mp

ow

erm

ent

2.4

7

0.5

7

0.1

3

-0.0

2

-0.0

4

-0.0

7

-0.1

1

-0.1

9

-0.0

5

0.3

0

0.5

0

0.4

3

0.4

4

0.5

4

0.4

4

0.4

0

0.6

6

0.52

16

. C

ontr

act

Per

form

ance

2

.35

0

.86

0

.89

-0

.14

-0

.08

0

.06

-0

.08

-0

.09

0

.00

0

.21

0.3

6

0.3

4

0.4

3

0.4

6

0.3

0

0.2

5

0.5

6

0.5

7

0.77

Note

s: M

= m

ean c

onst

ruct

sco

re (

unw

eigh

ted

); SD

= s

tand

ard

dev

iati

on; SK

= s

kew

nes

s;

a : N

um

ber

s on

th

e dia

gonal

(in

italic)

rep

rese

nt

the

squar

e ro

ot

of

the AVE

. O

ff-d

iagon

al n

um

ber

s re

pre

sen

t th

e co

rrel

atio

ns

amon

g c

on

stru

cts.

56

Table 4: Partial Lea

st S

quare

(PLS) Estim

ation R

esults fo

r Direc

t Effec

ts

Str

uct

ura

l p

aths

Hyp

oth

esis

P

LS

es

tim

ate

Sta

nd

ard

d

evia

tio

n

Beh

avio

ral

alig

nm

ent →

Co

ntr

act

per

form

ance

H

1

0.4

0∗∗∗

0.1

1

Info

rmat

ion a

lig

nm

ent →

Co

ntr

act

per

form

ance

H

2

0.1

3∗

0.0

9

Mat

eria

l &

eq

uip

men

t al

ign

men

t →

Co

ntr

act

per

form

ance

H

3

-0.0

0

0.0

7

Co

mp

lem

enta

ry c

om

pet

enci

es →

Beh

avio

ral

alig

nm

ent

H4

a 0

.23∗∗∗

0.0

9

Co

mp

lem

enta

ry c

om

pet

enci

es →

Info

rmat

ion a

lign

men

t

H4

b

0.4

2∗∗∗

0.1

0

Co

mp

lem

enta

ry c

om

pet

enci

es →

Mat

eria

l &

eq

uip

men

t al

ign

men

t

H4

c 0

.39∗∗∗

0.1

0

Co

ngru

ency

of

exp

ecta

tio

n o

f se

lf →

Beh

avio

ral

alig

nm

ent

H5

a 0

.32∗∗∗

0.0

9

Co

ngru

ency

of

exp

ecta

tio

n o

f se

lf →

Info

rmat

ion a

lig

nm

ent

H

5b

0

.10

0

.09

Co

ngru

ency

of

exp

ecta

tio

n o

f se

lf →

Mat

eria

l &

eq

uip

men

t al

ign

men

t H

5c

0.1

4∗

0.1

0

Co

ngru

ency

of

exp

ecta

tio

n o

f o

ther

→

Beh

avio

ral

alig

nm

ent

H6

a 0

.34∗∗∗

0.0

9

Co

ngru

ency

of

exp

ecta

tio

n o

f o

ther

→

Info

rmat

ion a

lig

nm

ent

H

6b

0

.14∗

0.0

9

Co

ngru

ency

of

exp

ecta

tio

n o

f o

ther

→

Mat

eria

l &

eq

uip

men

t al

ign

men

t H

6c

0.0

9

0.1

0

∗∗∗:

Sig

nif

ican

t at

.0

01

sig

nif

ican

ce l

evel

(tw

o-t

aile

d);

∗∗:

sig

nif

ican

t at

.0

1 s

ignif

ican

ce l

evel

(tw

o-t

aile

d);

∗:

sign

ific

ant

at .

05

sig

nif

ican

ce l

evel

(tw

o-t

aile

d).

57

Table 5 P

artia

l Lea

st S

quare

(PLS) Estim

ation R

esults fo

r M

edia

ting E

ffec

ts of Control and E

mpower

men

t

B

ehav

iora

l A

lign

men

t

Info

rmat

ion A

lig

nm

ent

M

ater

ial

& E

quip

men

t A

lig

nm

ent

M

od

el 1

Mo

del

2

M

od

el 3

Mo

del

4

M

od

el 5

Mo

del

6

Variable

b

s.e.

b

s.e.

b

s.e.

b

s.e.

b

s.e.

b

s.e.

Co

mp

lem

enta

ry

com

pet

enci

es

0

.26∗∗∗

0.0

9

0

.16∗∗

0.1

0

0

.40∗∗∗

0.1

0

0

.27∗∗∗

0.1

1

0

.41∗∗∗

0.0

9

0

.37∗∗∗

0.1

2

Co

ngru

ency

of

exp

ecta

tio

n I

0

.31∗∗∗

0.0

9

0

.25∗∗∗

0.1

1

0

.14∗∗

0.0

9

0

.05

0

.07

0.1

0∗

0.0

8

0

.08

0

.09

Co

ngru

ency

of

exp

ecta

tio

n 2

0

.34∗∗∗

0.1

0

0

.30∗∗∗

0.1

1

0

.13∗∗

0.0

9

0

.08

0

.10

0.0

7

0.0

8

0

.05

0

.09

Age

-0.0

3

0.0

6

-0

.07

0

.07

-0.0

9∗

0.0

7

-0

.15∗

0.0

9

0

.13∗

0.0

9

0

.11∗

0.0

9

Ed

uca

tio

n

-0.0

3

0.0

5

-0

.02

0

.05

-0.1

0

0.0

8

-0

.07

0

.06

-0.2

2∗∗

0.0

9

-0

.20∗∗

0.1

0

Gen

der

0

.03

0

.05

0.0

1

0.0

5

-0

.18∗∗

0.1

0

-0

.21∗∗

0.1

0

0

.00

0

.06

-0.0

2

0.0

8

Inco

me

-0.0

3

0.0

5

0

.02

0

.06

0.1

1

0.0

9

0

.14∗

0.0

9

0

.02

0

.07

0.0

2

0.0

7

Mar

ital

sta

tus

0.0

5

0.0

7

0

.11

0

.09

-0.0

4

0.0

8

-0

.01

0

.08

-0.0

5

0.0

7

-0

.05

0

.09

Rac

e -0

.09

0

.09

-0.1

2

0.1

1

0

.24∗∗

0.1

0

0

.22∗∗

0.1

0

-0

.10

0

.10

-0.1

0

0.1

1

Inte

ract

ion

-0.0

6

0.0

6

-0

.07

0

.06

-0.0

9∗

0.0

9

-0

.11∗

0.0

8

0

.12∗

0.1

0

0

.11∗

0.1

0

Co

ntr

ol

0

.06

0

.07

0

.24∗∗

0.1

0

0.1

3∗

0.1

1

Em

po

wer

men

t

0.2

2∗∗

0.0

9

0.1

3∗

0.1

4

-0.0

3

0.1

2

0

.52

0

.57

0

.34

0

.41

0

.35

0

.37

0.0

5

0

.07

0.0

2

∗∗∗:

Sig

nif

ican

t at

.0

01

sig

nif

ican

ce l

evel

(tw

o-t

aile

d);

∗∗:

sig

nif

ican

t at

.0

1 s

ignif

ican

ce l

evel

(tw

o-t

aile

d);

∗:

sign

ific

ant

at .

05

sig

nif

ican

ce l

evel

(tw

o-t

aile

d).

58

Table 6 E

ffec

ts of Co-p

roduct

ion Inputs on C

ontr

ol and E

mpower

men

t

B

ehav

iora

l A

lign

men

t

Info

rmat

ion A

lig

nm

ent

M

ater

ial

& e

quip

men

t A

lign

men

t

C

ontr

ol

E

mp

ow

erm

ent

C

ontr

ol

E

mp

ow

erm

ent

C

ontr

ol

E

mp

ow

erm

ent

Variable

b

s.e.

b

s.e.

b

s.e.

b

s.e.

b

s.e.

b

s.e.

Co

mp

lem

enta

ry

com

pet

enci

es

0

.35∗∗∗

0.0

9

0

.33∗∗∗

0.1

2

0

.35∗∗∗

0.1

0

0

.32∗∗∗

0.1

2

0

.35∗∗∗

0.0

9

0

.31∗∗∗

0.1

2

Co

ngru

ency

of

exp

ecta

tio

n o

f se

lf

0.1

9∗∗

0.0

9

0

.20∗∗

0.1

1

0

.19∗∗

0.0

9

0

.22∗∗∗

0.1

0

0

.19∗∗

0.0

9

0

.22∗∗

0.1

2

Co

ngru

ency

of

exp

ecta

tio

n o

f o

ther

0

.14∗

0.0

9

0

.18∗∗

0.1

0

0

.14∗

0.0

9

0

.17∗∗

0.1

1

0

.15∗

0.1

0

0

.18∗∗

0.1

1

∗∗∗:

Sig

nif

ican

t at

0.0

01

sig

nif

ican

ce l

evel

, ∗∗:

signif

ican

t at

0.0

1 s

ignif

ican

ce l

evel

, ∗:

sig

nif

ican

t at

0.0

5 s

ign

ific

ance

lev

el.

59

Figure 1: The Dynamic relationship between alliance structure, core value transformations and

alliance management for Value Co-production

Figure 2: A model of contract performance in an outcome-based equipment service

60

Fig

ure

3 S

tructu

ral m

odel of co

ntract p

erfo

rm

ance

in outcom

e-base

d equip

men

t se

rvice