An empirical investigation of transaction dynamics in online surplus networks: A complex adaptive system perspective

• Author: Suvrat Dhanorkar,Kevin Linderman,Yusoon Kim
• Date: 01 March 2019
• DOI: http://doi.org/10.1002/joom.1006
• Published date: 01 March 2019

ORIGINAL ARTICLE

An empirical investigation of transaction dynamics in online

surplus networks: A complex adaptive system perspective

Suvrat Dhanorkar

1

| Yusoon Kim

2

| Kevin Linderman

3

1

Supply Chain Management, Smeal College

of Business, Pennsylvania State University,

University Park, Pennsylvania

2

Operations Management, College of

Business, Oregon State University,

Corvallis, Oregon

3

Supply Chain and Operations, Carlson

School of Management, University of

Minnesota, Minneapolis, Minnesota

Correspondence

Suvrat Dhanorkar, Supply Chain

Management, Smeal College of Business,

Pennsylvania State University, University

Park, PA 16802.

Email: ssd14@psu.edu

Handling Editors: Anand Nair and Felix

Reed-Tsochas

Abstract

Online material and waste exchanges (OMWEs) provide an online platform connecting

suppliers of surplus material with potential buyers. These exchanges aim to improve

the environment by helping industrial organizations repurpose surplus material and

avoid landfill disposal. OMWEs represent an emerging surplus-driven supply network,

which exhibits different internal complexities and dynamics from traditional supply

networks, with similarly distinct transactional patterns and outcomes. Drawing o n com-

plex adaptive system (CAS) theory, this study investigates how the complex network

adapts to alter the likelihood of transactions between buyers and suppliers. Using

data from MNExchange.org, an OMWE operating in the US state of Minnesota, we

observe that, at the node level, buyers adapt their searches for products over time to

increase transaction success; at the dyadic level, buyer–supplier pairing patterns adapt

over time through homophilous relations to facilitate negotiations and increase transac-

tion success; and at the network level, the entire exchange system structurally self-

organizes to increase transaction rates. Throughout, buyers’competition influences

transaction success, contingent on whether the product has been on the market for a

long time, and buyers with more experience more quickly identify favorable conditions

(among products and suppliers) leading to higher transaction success than less experi-

enced competitors. Overall, the results demonstrate multilevel network emergence, in

which complex, adaptive, and longitudinal buyer–supplier interactions resolve uncer-

tainty and increase transactions. These findings disentangle OMWEs' operation to

allow managers and policymakers to increase the overall buyer–supplier transaction

rates with an eye toward improved environmental outcomes.

KEYWORDS

online material exchanges, surplus networks, surplus-driven supply network, sustainability, complex

adaptive systems

1|INTRODUCTION

Each year, firms accumulate surplus materials such as indus-

trial packaging (e.g., boxes, containers), mixed electronics

(e.g., lamps, computers), unused raw materials (e.g., wood,

rubber), and by-products (e.g., chemicals, leather). In the

past, they might have given little thought to sending such

surplus to landfills, but today we know that landfills gener-

ate toxins, leachate, and greenhouse gas, all of which nega-

tively impact the environment. The Environmental

Protection Agency (EPA) estimates that landfills emit over

18% of methane gas in the United States, and methane is

21 times stronger than carbon dioxide in terms of its global

warming effect. In 2013, the United States generated about

DOI: 10.1002/joom.1006

160 © 2019 Association for Supply Chain Management, Inc. wileyonlinelibrary.com/journal/joom J Oper Manag. 2019;65:160–189.

254 million tons of industrial surplus, the bulk of which was

deposited in landfills.

1

In an emerging alternative, compa-

nies can work to find buyers to reuse or repurpose the sur-

plus material, mitigating its negative environmental impact.

However, finding buyers for surplus material often falls out-

side the purview of the typical supply chain management –

after all excess material is by definition “unwanted.”

Recently, Online Material and Waste Exchanges (OMWEs)

have emerged to help suppliers of excess material connect with

potential buyers and avoid landfill disposal.

2

OMWEs provide

an online platform networking registered industrial suppliers

and buyers. Suppliers list their surplus material, and interested

buyers contact the supplier for additional information. Multiple

OMWEs have emerged across the United States, including

MNExchange.org in Minnesota, the Reuse Marketplace in

New England, the Resource Exchange Network for Eliminating

Waste (RENEW) in Texas, and the Material Trader in Pennsyl-

vania, and the EPA estimates that OMWEs help divert billions

of pounds of industrial waste away from landfills or incinera-

tion plants. The growth and environmental benefits of OMWEs

hinge on connecting otherwise unrelated buyers and suppliers

of surplus material to improve the environment.

Exploratory studies have investigated the factors that influ-

ence exchanges in OMWEs (e.g., Dhanorkar, Donohue, &

Linderman, 2015). However, research has not yet examined

the implications of the unique network structure and the emer-

gent buyer–supplier behavior, which is important for several

reasons. First, understanding the networking structure for trans-

actions is critical because the surplus material in OMWEs is

generated without knowing its demand a priori. Second, in

OMWEs, the same buyers and suppliers infrequently interact,

yet their emerging collective behavior plays a critical role in

determining transaction rates. This involves understanding the

complex internal network dynamics and how it evolves over

time. Third, OMWEs historically have had low transaction

rates; to increase those rates and mitigate environmental

damage, it is important to understand how the emerging net-

working patterns and dynamics influence exchanges. Fourth,

OMWEs, when compared to more traditional online markets

(e.g., Amazon.com or eBay), typically involve lower volume,

unbranded products, and buyers' limited access to product

information. That is, buyers operate under higher uncertainty

with regard to the nature of the products, the structure of their

negotiations with suppliers, and potential competition with

other buyers. In aggregate, this adds layers of complexity to

achieve successful transactions in the network.

To better understand the unique structure and behavior of

OMWEs, we first conceptualize the surplus-driven supply

network (SDSN) vis-à-vis a traditional supply network. In an

SDSN, the network activities are focused on finding demand

for the surplus material after it has been generated. That is,

suppliers tap into a network of potential buyers to see whether

there is a market for their surplus material. In contrast, a tradi-

tional supply network revolves around activities to better

match supply with demand (Fisher, 1997). This often takes

the form of forecasting demand toward making the appropri-

ate supply decisions. In brief, then, a traditional supply net-

work manages supply given demand, whereas an SDSN

manages demand given supply. As a result, this study investi-

gates how the com plex and emergent b ehavior of this t ype of

network affects transactions of surplus material. In particular,

drawing on Complex Adaptive System (CAS) theory, we

examine how the different levels (node, dyad, and network)

of complexity inform the emerging network behavior and the

likelihood of buyer–supplier transactions. More specifically,

we examine the node-level effects of buyers' search strategies

for products, the dyad-level effects of industry homophily

between buyers and suppliers when negotiating for products,

and network-level competitive effects. In doing so, we con-

sider how different types of uncertainty are associated with

the behavioral complexity at each of three systemic levels to

affect the likelihood of transaction. Furthermore, we examine

how behavior of the exchange system adapts over time.

The analysis uses data from MNExchange.org, an OMWE

located in the US state of Minnesota, to examine how the

buyers adapt under uncertainties to influence transaction suc-

cess. Buyers and suppliers must register to join the network.

This creates a rather stable membership and an enduring net-

work in which participants' behavior can be observed over

time. Every time a buyer makes an inquiry about a product

listed on MNExchange.org, it forms a link with a supplier; this

may (or may not) lead to a transaction. The results show that,

at the node level, when buyers follow a depth search strategy

(i.e., repeated inquiries or information requests to the same sup-

plier), they will more likely have a successful transaction for a

raw material product. In contrast, for finished goods items,

buyers will more likely have a successful transaction when they

follow a breadth search strategy (i.e., inquires or information

requests to several different suppliers of comparable products).

The analyses also reveal that buyers adapt their use of search

strategies to increase transaction success over time. At the dyad

level, the industry homophily (i.e., preference to exchange with

partners in the same industry) increases the likelihood of trans-

action when the supplier offers a product for a “price,”but not

when it is “free.”Similar organizational and institutional traits

between buyer–supplier dyads facilitate a transaction for prod-

ucts listed for a “price”when compared to those offered for

“free.”The results also show that as buyers accumulate experi-

ences in the network, they will increasingly seek out homophi-

lous links with suppliers that offer products for a price. Finally,

at the network level, competition among buyers generally

reduces the likelihood of transaction for individual buyers,

unless the product has been on the market for a long t ime. In

other words, persistent competition among potential buyers has

DHANORKAR ET AL.161