Lean Production implementation, Cloud-Supported Logistics and Supply Chain Integration: interrelationships and effects on business performance

• DOI: https://doi.org/10.1108/IJLM-02-2019-0052
• Pages: 629-663
• Date: 17 July 2020
• Published date: 17 July 2020
• Author: Luciano Novais,Juan Manuel Maqueira Marín,José Moyano-Fuentes
• Subject Matter: Management science & operations,Logistics

Lean Production implementation,

Cloud-Supported Logistics and

Supply Chain Integration:

interrelationships and effects on

business performance

Luciano Novais

Universitat Politecnica de Valencia, Valencia, Spain

Juan Manuel Maqueira Mar



ın

Department of Business Administration, Universidad de Jaen, Jaen, Spain, and

Jos

e Moyano-Fuentes

Department of Business Organization,

Marketing and Sociology, Universidad de Jaen, Jaen, Spain

Abstract

Purpose –With support from the dynamic capabilities theory, this paper examines the role of Cloud

Computing technology use in logistics (Cloud-Supported Logistics) and its effect on business results in Lean

manufacturing management (Lean Production implementation) and Supply Chain Integration contexts.

Design/methodology/approach –Using the survey method, a random sample of 260 companies in

intermediate positions in their supply chains was gathered from a population of 1,717 Spanish companies and

used to test five hypotheses. The data were collected by telephone survey using a computerisedsystem with a

response rate of 15.6% (260 valid questionnaires). Structural equation modelling was used to test the five

proposed hypotheses.

Findings –The findings indicate that Cloud-Supported Logistics use plays an important role in achieving

better business results in Lean Production environments. Lean Production has been found to have both a direct

effect and an even more powerful indirect effect on performance through the Cloud-Supported Logistics and

Supply Chain Integration that these technologies produce. Supply Chain Integration is also found to have a

mediating effect in the Cloud-Supported Logistics–performance relationship.

Originality/value –This study is valuable for academics and practitioners as it provides evidence of the

relevant role played by Cloud-Supported Logistics in Lean Production implementation contexts. Cloud-

Supported Logistics and Lean Production are strategically and operationally linked and their joint use results

in Supply Chain Integration and better business performance.

Keywords Lean Production implementation, Cloud-Supported Logistics, Supply Chain Integration, Business

performance

Paper type Research paper

1. Introduction

Market dynamism drives companies to be more efficient so as to produce high-quality

products at a lower cost and in the shortest possible time (Moyano-Fuentes et al., 2012b). This

is the goal of companies when they implement Lean Production (LP) (Moyano-Fuentes et al.,

2012b). Information technology (IT)-related capabilities have been found to play a major role

in improving business performance when LP is implemented (Brunn and Mefford, 2004) and

in integrating the supply chain process (Bruque et al., 2015).

LP, Cloud-

Supported

Logistics and

SCI

629

The authors acknowledge the financial support of Conselho Nacional de Desenvolvimento Cient



ıfico e

Tecnol

ogico (CNPq) of Brazil and the Spanish Ministry of Economy and Competitiveness Research

Project PID2019-106577GB-100.

The current issue and full text archive of this journal is available on Emerald Insight at:

https://www.emerald.com/insight/0957-4093.htm

Received 13 February 2019

Revised 16 July 2019

14 October 2019

18 February 2020

2 May 2020

Accepted 15 June 2020

The International Journal of

Logistics Management

Vol. 31 No. 3, 2020

pp. 629-663

© Emerald Publishing Limited

0957-4093

DOI 10.1108/IJLM-02-2019-0052

Womack et al. (1990) define LP as a systematic approach to the identification and

elimination of waste and low or zero value-added activities through continuous improvement.

In this manufacturing context, IT can facilitate production planning, demand and supply

planning and accounting and customer service, among others (Ghaffari et al., 2014;Rai et al.,

2015). In recent years, a new IT paradigm called Cloud Computing has been rapidly adopted

by companies as it offers cost and flexibility advantages and can be applied in different

functional areas, including logistics (Subramanian et al., 2015). To be exact, Cloud-Supported

Logistics is the application of Cloud Computing IT to the logistics business function. Some

studies show that IT such as Cloud Computing can affect the internal aspects of the

organisation’s productive structure and the interconnections and functionality of inter-

organisational configurations (Moyano-Fuentes et al., 2012a;Vermula and Zsifkovits, 2016).

More specifically, Cloud-Supported Logistics could enable effective and efficient integration

of the businesses and systems with which it interacts (suppliers, consumers, logistics

operators) (Li et al., 2013;Subramanian et al., 2015). Another way to improve business results

and competitiveness is through Supply Chain Integration (SCI) is a capability that consists of

integrating physical, information and financial flows (Rai et al., 2006) and rapidly sharing

information and activities across the value chain as a way of promoting cooperative

behaviour between chain agents (Devaraj et al., 2007;Zhao et al., 2011).

The literature has analysed the role that IT plays in LP contexts and the way that both of

these impact business results (Pinho and Mendes, 2017). IT’s power to achieve SCI has also

been analysed (Yu et al., 2017). But Cloud Computing is a new phenomenon that has had a

rapid uptake in companies, where it is being applied to the supply chain to achieve SCI

(Bruque et al., 2015,2016). It might be of great interest for both theory and practice to jointly

analyse the relationships between these three efficiency-seeking mechanisms (LP-IT-SCI) and

the effect that they have on business results. This is especially true if the analysis is focused

on the new reality that Cloud Computing use in the supply chain represents.

The previous literature has addressed the three relationships separately: LP

implementation–IT (Brunn and Mefford, 2004;Ward and Zhou, 2006;Riezebos et al., 2009),

IT–SCI (Gunasekaran and Ngai, 2004;Li et al., 2009;Prajogo and Olhager, 2012;Yu et al.,

2017) and Cloud–SCI (Bruque et al., 2015,2016;Maqueira et al., 2019;Novais et al., 2019).

However, no studies have been identified that address all three variables together and their

relationship to business performance. This joint analysis could be relevant since

organisational factors such as LP implementation and the technological capabilities that

derive from the use of Cloud Computing could have multiplier effects on SCI and business

performance. LP is a management system that seeks efficiency and so has a positive impact

on business performance (Van der Vaart et al., 2012;Stump and Badurdeen, 2012), while

Cloud Computing is an IT that achieves greater efficiency than previous technologies and has

also been proven to have a direct effect on logistics activities and SCI (Bruque et al., 2015;

Trappey et al., 2016). The literature has recently identified the potential of Cloud Computing

applied to the supply chain (Cloud-Supported Logistics) and to SCI, especially (Novais et al.,

2019). So, companies that use LP may be induced to use Cloud-Supported Logistics in order to

make further gains in efficiency.

This study, therefore, aims to examine more closely the interrelationships between LP,

Cloud-Supported Logistics and Supply Chain Integration (SCI), and their impacts on business

performance. From a theoretical point-of-view, dynamic capabilities theory (Teece, 1988;

Teece et al., 1997) is used, as SCI is a dynamic capability (Oliveira et al., 2014). This study is

valuable for academics and practitioners as it supports the role played by the strategic and

operational link between the resource (Cloud-Supported Logistics) and the dynamic

capability (SCI) and the notion that the LP-IT combination results in dynamic capabilities

(Teece, 1988;Teece et al., 1997) that subsequently lead to better business performance. This

study, therefore, aims to answer the following research questions: (1) what kind of

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relationship exists between LP implementation and Cloud-Supported Logistics and how does

it affect company performance? (2) what role does Cloud-Supported Logistics play in business

performance when implemented in conjunction with LP and SCI?

To achieve this objective, the paper has been structured into six sections preceded by this

introduction. The second section presents the background to the research and the third

section states the research hypotheses. The fourth section describes the methodology used.

The obtained results are presented in the fifth section. Section six offers a discussion. Finally,

section seven sets out the conclusions, implications and lines of future research.

2. Theoretical background

In this section, firstly, the key concepts used in the article’s theoretical model are stated. Then,

the dynamic capabilities theory, which underlies the hypotheses, is described. Thirdly, we

show the way that the literature has analysed the relationships between the key concepts,

which acts as the basis for the way that the hypotheses are subsequently addressed.

2.1 Key factors: conceptualisation

This section describes the conceptualisation of the key factors in this research (LP, Cloud-

Supported Logistic, SCI and business performance).

2.1.1 Lean Production. LP is defined as a systematic approach to the identification and

elimination of waste and low or zero value-added activities in the manufacturing function

through continuous improvement (Krafcik, 1988;Womack et al., 1990;Womack and Jones,

1996). LP extends to manufacturing operations, distribution and product development and

processing times (Hopp and Spearman, 2004;Holweg, 2007;Stump and Badurdeen, 2012).

There is some consensus in the literature that practices commonly associated with LP are:

Manufacturing Cells (MC), i.e. the grouping of workers and machines to perform specialised

operations; Total Quality Management (TQM), i.e. holistic quality consideration; Total

Productive Maintenance (TPM), i.e. the continuous improvement of equipment effectiveness

to create a favourable environment between workers and equipment; Just In Time (JIT), i.e.

producing and delivering components when they are needed and Human Resources

Management (HRM) (Cagliano et al., 2006;Shah et al., 2008;Moyano-Fuentes et al., 2012b).

Moyano-Fuentes et al. (2012a) have operationalised the concept of LP in a measurement

instrument that includes these practices. The instrument contains three MC-related variables

(efficient layout, manufacturing cells and reduced inventory level in rapid manufacturing);

three TPM-related variables (Single Minute Exchange of Die or SMED, TPM use and regular

maintenance of all equipment); two JTI-related variables (JTI and Kanban system use); and

one TQM-related variable (TQM use) (Moyano-Fuentes et al., 2012a). This measure has been

used in recent studies with the same LP concept (Uhrin et al., 2017).

2.1.2 Cloud-Supported Logistics. In the manufacturing context, IT may be able to facilitate

production planning, demand and supply planning and accounting and customer service,

among others (Ghaffari et al., 2014;Rai et al., 2015). Cloud Computing is an IT-based tool, a set

of virtualised and distributed resources that are diffuse, ubiquitous and geographically

dispersed that can be accessed on-demand using web-based technologies (Mell and Grance,

2011;Hayes, 2008;Fingar, 2009;Buyya et al., 2011). More precisely, Cloud-Supported

Logistics is the application of cloud systems to the area of logistics. In Cloud-Supported

Logistics, the information that supports the logistics process is no longer stored on local

systems but hosted and run on distributed networks that can be accessed through a web

browser (Wang et al., 2012;Li et al., 2013;Nowicka, 2014). Cloud-Supported Logistics offers

high computing power and storage capacity and is a powerful tool that can improve logistics

services and make enterprises more efficient than earlier IT systems did (Li et al., 2013;

Oliveira et al., 2014;Trappey et al., 2016). In the literature, one specific type of Cloud

Computing is operationalised through a single variable (Bruque et al., 2016).

LP, Cloud-

Supported

Logistics and

SCI

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