Incentivizing supplier participation in buyer innovation: Experimental evidence of non‐optimal contractual behaviors

• DOI: http://doi.org/10.1016/j.jom.2017.12.001
• Published date: 01 January 2018
• Author: Tingting Yan,Dina Ribbink,Hubert Pun
• Date: 01 January 2018

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Journal of Operations Management

journal homepage: www.elsevier.com/locate/jom

Incentivizing supplier participation in buyer innovation: Experimental

evidence of non-optimal contractual behaviors

Tingting Yan

a,1

, Dina Ribbink

b,∗,1

, Hubert Pun

c,1

a

Mike Ilitch School of Business, Wayne State University, Detroit, MI, USA

b

College of Business, Oregon State University, Bend, OR, USA

c

Ivey Business School, Western University Canada, London, ON, Canada

ARTICLE INFO

Accepted by: Dr. Daniel R Guide

Keywords:

Behavioral experiment

Contract design

New product development (NPD)

Risk aversion

Supplier involvement

ABSTRACT

Original equipment manufacturers increasingly involve suppliers in new product development (NPD) projects.

How companies design a contract to motivate supplier participation is an important but under-examined em-

pirical question. Analytical studies have started to examine the optimal contract that aligns buyer-supplier in-

centives in joint NPD projects, but empirical evidence is scarce about the actual contracts offered by buying

companies. Bridging the analytical and empirical literature, this paper compares optimal contracting derived

from a parsimonious analytical model with actual behaviors observed in an experiment. In particular, we focus

on how project uncertainty, buying company effort share, and buyer risk aversion influence three contractual

decisions: total investment level, revenue share and fixed fee. Our results indicate significant differences be-

tween the optimal and actual behaviors. We identify various types of non-optimal contractual behaviors, which

we explain from a risk aversion as well as a bounded rationality perspective. Overall, our findings contribute to

the literature by showing that (1) the actual contractual behaviors could differ significantly from the optimal

ones, (2) the actual contract design is sensitive to changes in project uncertainty and buying company effort

share, and (3) the significant roles of risk aversion and bounded rationality in explaining the non-optimal

contractual behaviors.

1. Introduction

Original equipment manufacturers (OEM) are more and more re-

lying on suppliers for innovations. In a 2015 CAPS research survey,

83% of responding companies either had or were planning to have

formal supplier innovation programs in place so as to capture valuable

ideas and information from suppliers (Jennings, 2015). However, there

is mixed empirical evidence regarding the effectiveness of supplier in-

volvement for enhancing buying company NPD performance (Primo

and Amundson, 2002). To explain why, the empirical literature has

mostly focused on pre-contract strategies, such as supplier base ratio-

nalization, supplier integration, supplier selection (Petersen et al.,

2005), or post-contact tactics, such as supplier involvement timing,

supplier design responsibility, or project execution (Parker et al., 2008;

Yan and Dooley, 2014). Relatively less attention has been focused on

the contracting process that the buying company uses to motivate

supplier participation, which seems to imply an assumption: a supplier

is always willing to participate in buyer innovation projects irrespective

of the contract. This assumption is problematic because a supplier, as an

autonomous organization, could reject a buying company's offer that is

either too risky or does not produce enough return for the supplier,

especially when the supplier possesses valuable resources for buying

company innovation (Barney, 2012). Of the few empirical studies that

examine contract design in innovation, the focus has been on com-

paring the effectiveness of fixed-price and flexible contracts (cost

sharing or performance based) in various task contexts (Carson et al.,

2006; Gefen et al., 2008; Gopal and Koka, 2010; Gopal and

Sivaramakrishnan, 2008). However, even if a certain type of contract

performs better from a buying firm perspective, that does not mean a

supplier necessarily sees the value of the contract and ultimately ac-

cepts the contract. Therefore, one empirical question still remains un-

answered: how does a buying company determine contractual para-

meters (i.e., fixed fee, revenue share, etc.) when motivating a supplier

to accept the contract in a joint NPD context?

The analytical contract management literature has extensively stu-

died contractual coordination in a buyer-supplier production context.

The focus of this stream of work is on the design of a contract, specified

by parameters, such as revenue share, fixed fee, investment levels,

https://doi.org/10.1016/j.jom.2017.12.001

Received 14 March 2016; Received in revised form 13 November 2017; Accepted 18 December 2017

∗

Corresponding author.

1

All authors contributed equally to the paper.

E-mail addresses: Tingting.yan@wayne.edu (T. Yan), ribbinkd@oregonstate.edu (D. Ribbink), hpun@ivey.ca (H. Pun).

Journal of Operations Management 57 (2018) 36–53

Available online 16 February 2018

0272-6963/ © 2017 Elsevier B.V. All rights reserved.

T

quantity discounts, that maximize supply chain utility by aligning

buyer and supplier incentives (Cachon, 2003). Within this stream of

work, there is an emerging set of studies that examines contractual

coordination in an inter-firm joint innovation context, which represents

a more tacit and uncertain knowledge exchange context when com-

pared to the traditional product exchange settings (Yan and Kull, 2015).

Most of these studies assume risk-neutral decision makers, which has

been shown to be unrealistic. Decision makers are generally risk averse

according to the decision making under uncertainty literature (March

and Shapira, 1987). In particular, a risk averse decision maker prefers a

certain profit to a risky profit, even when the certain and risky profits

have the same expected value (Gan et al., 2011). In fact, Ülkü et al.

(2007) points out that “by not negotiating on risk, parties leave money

on the table”(p.238). Given the possible influences of risk-sensitivity on

contractual designs, it is necessary to see how buyer risk aversion in-

fluences the contractual design, particularly, in a highly uncertain

supply chain context, such as a joint new product development project

(Ülkü et al., 2007). In addition, very few “optimal”contractual beha-

viors specified in the analytical NPD literature have been empirically

validated. By saying “contractual behaviors”, we refer to the relation-

ship between a contractual parameter and a contextual variable, or how

a particular contractual decision, such as fixed fee, changes in relation

to changes in a contextual variable, such as project uncertainty, effort

split, and buyer risk aversion. Given the fact that decision makers have

individual biases (i.e. risk aversion) and bounded rationality, it is im-

portant to examine whether a buying company decision maker, shor-

tened as buyer hereafter, behaves optimally when offering a contract to

a supplier, and if not, how and why the actual behavior differs from the

optimal one (Simon, 1982).

To fill the above literature gaps, we adopt a multi-method approach

to examine how a buyer designs a contract to motivate supplier parti-

cipation in a NPD project. Specifically, we want to answer two ques-

tions: (1) How do the characteristics of a NPD project context and risk

aversion of a buyer influence the optimal and actual contractual behaviors?

(2) Do the actual contractual behaviors of a buyer match the optimal ones?

If not, why? We chose to focus on two contextual characteristics of an

inter-organizational NPD context, project uncertainty and buyer-sup-

plier effort split, which help differentiate a buyer-supplier NPD context

from a mass production context. Unlike a mass production context

which is usually about existing products, a NPD task faces significant

uncertainty because the new technology used for developing the pro-

duct could fail or the newly developed product may not perform well in

the market. Buying company effort share is another critical contextual

factor. In a mass production context, a supplier usually does the com-

plete job (100% supplying company effort share) in order to get com-

pensated by a buyer financially. In contrast, in a joint NPD project, a

buyer and a supplier could share the total development efforts, usually

in a way that is determined by the nature of the technology involved

and the skill sets of the two firms (Bhaskaran and Krishnan, 2009).

2

We answer the two questions by adopting a multi-method approach.

To answer the first question, we set up a mathematical model to see

how the two contextual variables and buyer risk aversion influence the

optimal contract design (Wacker, 1998). In particular, we focus on the

total cost and the transferrable payment of a typical buyer-supplier

contract, which is characterized by three contractual parameters (Katok

and Wu, 2009; Zhang et al., 2016). To capture the cost aspect, we look

at the investment level (the first parameter) that the buying company

and the supplier together need to commit to the project. Regarding the

transferrable payment between the two firms, we focus on revenue

share (the second parameter) and fixed fee (the third parameter), which

are two typical ways for the two firms to share revenue and cost from

the joint effort (Cachon, 2003). Then we run a behavioral experiment to

test hypotheses derived from the math model. By comparing the

mathematical and experimental results, we answer the second research

question.

This study contributes to the literature in two ways. First, we con-

tribute to the supplier involvement in NPD literature by examining how

project uncertainty, buying company effort share and buyer risk aver-

sion influence the optimal as well as actual contractual designs. Second,

we contribute to the behavioral operations management literature by

explaining the differences between the mathematical and experimental

results. In particular, we focus on two possible mechanisms to explain

non-optimal behaviors: (1) risk aversion, a type of individual biases,

which changes the utility functions to include not only the expected

profit but also a risk premium (Katok and Wu, 2009), and (2) bounded

rationality, or the fact that decision makers want to maximize their

expected profit, but make errors in doing so (Kahneman et al., 1982).

2. Literature review

There is abundant empirical evidence about benefits of involving

suppliers in an OEM's NPD process. Suppliers contribute to buyers'

product innovation efforts in a wide variety of ways. One major benefit

can be a more efficient development process (Kessler et al., 2000),

better product quality (McGinnis and Vallopra, 1999), and improved

product manufacturability (Swink, 1999). When engaged in the process

at the right time with an appropriate level of design responsibility,

suppliers contribute to the success of a buyer's NPD project by providing

access to advanced technology, helping understand design feasibility,

improving translation of customer requirements into manufacturing

specifications (Parker et al., 2008). More recent NPD studies start to

show challenges of managing suppliers in a buyer's innovation process

(Yan and Dooley, 2014; Yan and Kull, 2015). The difficulty of in-

tegrating two highly differentiated groups suggests the possibility of

inefficient process and low-quality designs (Yan and Dooley, 2013).

Furthermore, a buying company might involve suppliers that are nei-

ther willing nor capable to undertake collaborative NPD, which might

force buyers to spend limited project resources to motivate or develop

suppliers and thus deter project progress (Lawson et al., 2014). To

safeguard against these risks, the literature emphasizes a collaborative

buyer-supplier relationship as well as utilizing contractual governance

(Wang et al., 2011).

Most of these empirical studies, however, examine activities or

problems that happen after a supplier agrees to participate in a buying

company NPD project. Not much attention has been given to the con-

tracting process that is used to motivate supplier participation through

aligning buyer-supplier incentives. Some empirical work, however,

does allude to the importance of contract management in an innovation

context: MacCormack and Mishra (2015) show the significant influence

of contract choices on the relationship between partner integration and

alliance performance, while Ederer and Manso (2013) find that flexible

contracts within a firm provide the greatest incentives for employees to

innovate when compared to fixed-fee and pay-by-performance con-

tracts. There are also few studies that examine the effectiveness of fixed

price, cost/material sharing, and performance-based contracts vary in

different outsourcing contexts (Gefen et al., 2008; Gopal and Koka,

2010; Gopal and Sivaramakrishnan, 2008). Finally, the literature also

showed that relational governance complement formal contract in more

ambiguous, uncertain and complex innovation contexts (Carson et al.,

2006; Mani et al., 2012).

However, one empirical question remains unanswered: how does a

buying company determine contractual parameters (i.e., fixed fee,

revenue share, etc.) for aligning buyer-supplier incentives in a joint

NPD context? Disparate incentives, if not aligned, could demotivate the

participation of a capable supplier and/or cause the involvement of an

incapable supplier (adverse selection), and even if the supplier agrees to

get involved, could induce supplier opportunism (moral hazard), a

2

Although our model is built to study buyer-supplier NPD, it could be generalized to

any inter-organizational collaboration context where two parties jointly complete a

highly uncertain task.

T. Yan et al. Journal of Operations Management 57 (2018) 36–53

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