Logistics resources, capabilities and operational performance. A contingency and configuration approach
| DOI | https://doi.org/10.1108/IMDS-01-2018-0024 |
| Date | 11 March 2019 |
| Published date | 11 March 2019 |
| Pages | 230-250 |
| Author | Gaoyan Lyu,Lihua Chen,Baofeng Huo |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
Logistics resources, capabilities
and operational performance
A contingency and configuration approach
Gaoyan Lyu and Lihua Chen
Guanghua School of Management, Peking University, Beijing, China, and
Baofeng Huo
School of Management, Zhejiang University, Hangzhou, China
Abstract
Purpose –The purpose of this paper is to investigate how different logistics resources and resource patterns,
such as logistics infrastructure, logistics location, logistics knowledge and logistics information, affect
logistics capabilities and operational performance.
Design/methodology/approach –Based on data collected from 273 companies in China, this study
examines impacts of individual logistics resource dimensions on resource integration capability, customer
service capability and operational performance through contingency approach. Furthermore, three logistics
resource patterns are identified and linked with resource integration capability and operational performance
through configuration approach.
Findings –Contingency results show that different logistics resources have different impacts on resource
integration capability and operational performance. Configuration results reveal that companies’capabilities
and operational performance vary for different logistics resource patterns: the high-uniform pattern has a
better resource integration capability and operational performance than other patterns, while all logistics
resource patterns have similar customer service capability levels.
Research limitations/implications –Future studies should examine other resource capabilities and
performance indicators of companies and extend this study to other countries and regions.
Originality/value –This study contributes to the logistics resource literature through empirically
investigating relationships among logistics resources, resource integration capability and operational
performance using contingency approach, and through identifying different logistics resource patterns based
on configuration approach. The findings extend the logistics resource literature, particularly on research of
logistics parks in China.
Keywords China, Performance, Logistics capability, Logistics resource
Paper type Research paper
1. Introduction
A large number of logistics parks have been created in China over the past few decades with
the support of the government and large companies. According to a survey of the China
Federation of Logistics and Purchasing, in 2017, there were 475 logistics parks in the
country, and the average investment in each logistics park was $180m. In terms of logistics
performance, the total disposal capacity of logistics parks was 3,780,000 tons per square
kilometer per year. The average income of these logistics parks was 95m dollars, and
12 percent of parks had an annual revenue over 250m dollars (Su, 2017).
However, operational performance of companies in logistics parks is unbalanced.
The distribution of logistics parks is not concordant with demands of the wider society.
A burgeoning body of literature has examined the relationship between various logistics
resources and capabilities (Lai et al., 2008; Riley et al., 2016), and Table AI summarizes important
prior studies, but they do not systematically explore relationships in logistics parks.
Some investigate relationships among logistics service providers’resources, capabilities and
performance (Lai et al., 2008; Rifat, 2017; Shou et al., 2017; Yang and Lirn, 2017). From a
Industrial Management & Data
Systems
Vol. 119 No. 2, 2019
pp. 230-250
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-01-2018-0024
Received 17 January 2018
Revised 26 April 2018
15 June 2018
Accepted 20 June 2018
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
This research was supported by National Natural Science Foundation of China (No. 71525005). It is also
supported by Liantai Supply Chain System Research and Development Center at Peking University.
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IMDS
119,2
resource-based view (RBV) perspective, logistics resources and capabilities determine
performance. From the perspective of logistics parks, logistics information (Hazen and Byrd,
2012) and logistics knowledge (Ryoo and Kim, 2015) are related to performance. Meanwhile,
infrastructure improves overall environmental performance and promotes cooperation between
clustered companies, which creates an image of good integration and attracts additional
strongly performing companies to join (Yuan et al., 2010).
Furthermore, since the park is not supposed to be included in a supply chain, but in a
broader distribution network, it is essential to build logistics parks in good locations
with a superior labor pool and suitable social and geographical conditions to improve
logistics companies’operational performance. Thus, the choice of location directly
affects the implementation and fulfillment of operational activities within a supply
chain. Therefore, this study focuses on four logistics resources, two capabilities and
operational performance of companies in logistics parks. Logistics resources include soft
resources (i.e. logistics information and knowledge) and hard resources (i.e. logistics
infrastructure and location) and capabilities include customer service capability and
resource integration capability. Given previous studies mainly examine the effect of
individual dimensions of logistics resources, there is a notable gap in combing tangible
and intangible resources, and considering their joint effects on logistics capabilities and
operational performance based on logistics resource configurations.
This paper is organized as follows. The literature review for the research framework is
discussed in Section 2, and the research methodology is discussed in Section 3. Section 4
discusses results, and Section 5 provides implications and future research.
2. Literature review and proposed hypotheses
2.1 Definitions and dimensions of logistics resources
Based on RBV, a number of studies have identified logistics resources as rare, inimitable,
valuableand non-substitutable resourcesfor a company to achievecompany performance and
competitive advantages (Barney, 1991; Hartmann and Grahl, 2011; Lai et al., 2008). Logistics
resources are divided into tangibleand intangible resources (Lai et al., 2008; Yang et al., 2009;
Kamasak, 2017). Bothtangible (Huang et al., 2006) and intangible (Carmeli and Tishler, 2004)
resources are positively associated with a company’s capabilities and performance.
Logistics information is a major intangible resource. This information, which includes
real-time demand forecast information, purchasing information, inventory-level information,
production schedule information and material flow information, is unique and valuable for
individual organizations, and it plays an important role in improving 3PL services (Lai et al.,
2008; Huo et al., 2014; Chen et al., 2017), inventory management (Zhao et al., 2002), agility and
flexibility. In the context of logistics parks, logistics information becomes costly to imitate
because it is supported by proprietary technologies, and requires specific technical skills
and in some instances access to capital (Wong and Karia, 2010). Logistics knowledge is
another intangible resource. It is an inimitable and valuable building block for companies to
enable the development of core competencies, cope with challenges, manage complexities
and gain competitiveness (Ryoo and Kim, 2015). In this study, logistics knowledge refers to
knowledge about customers, services, technologies and problems involved in a particular
customer relationship, which helps companies to improve their performance (Rollins et al.,
2011). Not all processes produce valuable knowledge, thus organizing principles and related
human resources underlying the creation of knowledge can provide inimitable resources
(Blome et al., 2014).
Studies have identified logisticsinfrastructure as a tangible logistics resource (Yuan et al.,
2010). This infrastructure involves transport devices, IT platforms and other value-added
services. Althou gh today’s IT infrastructures are often modular and standardized, they
provide a company with a valuable and inimitable system of automatic routines shaped by
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