# Exploring the Link Between Lean Practices and Sources of Uncertainty in Supply Chain

Claudia del Monte, Matteo Zanchi, Paolo Gaiardelli

► To cite this version:

Claudia del Monte, Matteo Zanchi, Paolo Gaiardelli. Exploring the Link Between Lean Practices and Sources of Uncertainty in Supply Chain. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2021, Nantes, France. pp.748-757, 10.1007/978-3-030-85874-2_82. hal-04030344

HAL Id: hal-04030344

https://inria.hal.science/hal-04030344

Submitted on 15 Mar 2023

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_2.png" /></figure>

ifip

International Federation for Information Processing

This document is the original author manuscript of a paper submitted to an IFIP
conference proceedings or other IFIP publication by Springer Nature. As such, there
may be some differences in the official published version of the paper. Such
differences, if any, are usually due to reformatting during preparation for publication or
minor corrections made by the author(s) during final proofreading of the publication
manuscript.
# Exploring the link between lean practices and sources of
uncertainty in Supply Chain

Claudia Del Monte¹, Matteo Zanchi¹ and Paolo Gaiardelli¹ [0000-0002-2207-3628]

¹ Department of Management, Information and Production Engineering,
University of Bergamo, Viale Marconi 5, Dalmine (BG), Italy
c.delmonte@studenti.unibg.it,
matteo.zanchi@unibg.it,paolo.gaiardelli@unibg.it

**Abstract.** In an ever-changing environment, supply chains face countless risks generated by different sources of uncertainty. The adoption of lean management initiatives has been recognized as a viable and effective way for dealing with these uncertainties. However, since constant and rapid change of variables affecting supply chains risks nullifying or diminishing the potential benefits of lean initiatives, identification of proper lean practices emerges as essential to address their successful implementation. On these premises, this study proposes a model linking lean management practices with different forms of supply chain uncertainty. The model, built upon an analysis of the literature, is designed to help managers and practitioners in identifying and prioritizing lean actions to address issues within their supply chains.

**Keywords:** Lean Management, Supply Chain Management, Uncertainty, Literature review.

## 1 Introduction

Lean Management (LM) has been recognized over the years as one of the most promising approaches to help managers in controlling and managing complexity of a Supply Chain (SC) [1]. The reason why adoption of lean principles has gained attention in Supply Chain Management (SCM) resides in their ability to reduce the lead time from order receipt to customer delivery through the elimination of wastes and the simplification of processes [2]. Indeed, by acting on process instability, rigidity and opacity through standardization, implementation of a pull logic and promotion of collaboration, LM methods foster the creation of more responsive, flexible and efficient SCs [3].

Although LM plays a key role in the control of SCs, scientific studies are still lacking in providing a clear view of what lean actions should be taken to effectively deal with uncertainty in SCs. This critical issue is amplified by the difficulty in determining which practices are the most appropriate to respond to a particular type of uncertainty. Indeed, the increasing complexity of SCs, characterized by articulated configurations, rapid changes in customer choices and ever tighter timeliness, often makes ineffective the adoption of many lean approaches, based on fixed work cycles and
times and suitable for stable production [4]. Therefore, identifying the most appropri-
ate LM practices for uncertainty management in SC would help lean managers and
practitioners in better identifying and prioritizing their actions to address critical is-
sues characterizing SC operations. To answer this problem, this paper proposes a map
of the main LM practices to address sources of uncertainty in SCs. Consistently with
[5] the sources of uncertainty in SC are mapped around 14 categories, for each of
which a set of suitable LM practices, derived from an extensive analysis of literature
and grouped in accordance with [6], is proposed. The achieved map provides a struc-
tured and comprehensive overview of the relationship between uncertainty and LM
practices.

## 2 Methodology

This study is based on an extended analysis of the literature on SCM and its issues and LM practices. In particular, Web of Science and Google Scholars were the two databases used to collect relevant papers on the topics under exploration, considering a time frame restriction of the last ten years. Among the results, only English papers with full-text availability were taken into consideration. A forward snowballing research was paired with the backward citation analysis to avoid any weaknesses characterizing retrospective research. As a result of the adopted forward-backward snowballing analysis, 93 journal papers were finally reviewed. In addition, the research was deepened by consulting textbooks on Lean philosophy, Lean Management in operations and Lean Supply Chain.

## 3 Literature analysis

According to the purpose of the study, the literature analysis was built around two
main parts. The first part proposes an analysis of the current studies concerning
sources of uncertainty in SC, while the second part reports a description of lean prac-
tices for uncertainty management, extrapolated from the case studies available in the
scientific and managerial literature.

### 3.1 Sources of uncertainty in SC

A SC refers to all the parties involved, directly or indirectly, in satisfying a custom-
er's demand for a product or service [1]. It consists of multiple business partners who
work together and collaborate by sharing information, material and financial flows.
Therefore, a SC is usually faced with a considerable number of exogenous and en-
dogenous drivers of complexity originating from different sources which can arise
from network, process, range product, customer, supplier, organizational and infor-
mation complexities. The latter can be associated with fourteen sources of uncertainty
which in turn can be split into three main groups [5]: i) uncertainties originating from
the focal company; ii) uncertainties arising within the SC; iii) uncertainties external to
the SC. While uncertainties originating within the focal company and its partners are generally manageable, external uncertainties are often out of direct control. The list of SC sources of uncertainty is reported in Table 1.

<table><caption>**Table 1.** The sources of uncertainty in SC [5].</caption><thead><tr><th>Category</th><th>Source of uncertainty</th></tr></thead><tbody><tr><td rowspan="6">Uncertainties coming from the focal company</td><td>1. Product characteristic</td></tr><tr><td>2. Manufacturing process</td></tr><tr><td>3. Control/chaos</td></tr><tr><td>4. Decision complexity</td></tr><tr><td>5. Organizational/behavioral issues</td></tr><tr><td>6. IT/IS complexity</td></tr><tr><td rowspan="7">Uncertainties internal to the SC</td><td>7. End-customer demand</td></tr><tr><td>8. Demand amplification</td></tr><tr><td>9. Supplier</td></tr><tr><td>10. Parallel interaction</td></tr><tr><td>11. Order forecast horizon</td></tr><tr><td>12. Chain infrastructure and facilities</td></tr><tr><td>13. Environment</td></tr><tr><td rowspan="2">Uncertainties external to the SC</td><td>14. Disruption/natural disasters</td></tr></tbody></table>

## 3.2 Lean practices for uncertainty management

Several authors have proposed various models that combine the fields of LM and SC. Among others, the 8-pillar model [10] represents a unified Lean Supply Chain Management (LSCM) framework that permits an explicit definition of the set of elements that characterise this field. For its characteristics of completeness, this model can be considered as the best reference model to categorize LM practices for uncertainty management in SC, identified in literature and summarized in Table 2.A, Table 2.B and Table 2.C.

<table><caption>**Table 2A.** Lean practices for SC uncertainty classified according to the 8-pillar model [6].</caption><thead><tr><th>Category</th><th>Practices</th><th>References</th></tr></thead><tbody><tr><td rowspan="5">Information Technology Management (ITM)</td><td>ITM1 Effective and transparency information flow throughout supply chain</td><td>[6], [7]</td></tr><tr><td>ITM2 Modelling analysis and simulation tools</td><td>[6]</td></tr><tr><td>ITM3 Computer-aided decision-making supporting systems</td><td>[6]</td></tr><tr><td>ITM4 Enterprise resource planning system</td><td>[6], [8]</td></tr><tr><td>ITM5 ICT system (EDI)</td><td>[6], [8]</td></tr><tr><td>Supplier Management (SM)</td><td>SM1 Supplier evaluation and certification</td><td>[6], [7], [8]</td></tr></tbody></table>
<table><caption>**Table 2B.** Lean practices for SC uncertainty classified according to the 8-pillar model [6].</caption><thead><tr><th>Category</th><th>Practices</th><th>References</th></tr></thead><tbody><tr><td rowspan="4">Supplier Management (SM)</td><td>SM2 Strategic supplier development</td><td>[6], [7], [9]</td></tr><tr><td>SM3 Supplier proximity</td><td>[6]</td></tr><tr><td>SM4 Single source and reliable suppliers or few suppliers</td><td>[6]</td></tr><tr><td>SM5 Long-term supplier partnerships</td><td>[6]</td></tr><tr><td rowspan="4">Elimination of waste (EW)</td><td>EW1 Design for x/concurrent engineering</td><td>[2]</td></tr><tr><td>EW2 Standard products and processes</td><td>[6], [7]</td></tr><tr><td>EW3 5S</td><td>[6], [2], [9]</td></tr><tr><td>EW4 SMED</td><td>[6]</td></tr><tr><td rowspan="6">JIT Production (JITP)</td><td>JITP1 More simple lines/re-layout</td><td>[10]</td></tr><tr><td>JITP2 TPM</td><td>[7], [8]</td></tr><tr><td>JITP3 Levelling the workload</td><td>[2], [10]</td></tr><tr><td>JITP4 One-piece-flow</td><td>[6]</td></tr><tr><td>JITP5 Pull systems</td><td>[9], [10]</td></tr><tr><td>JITP6 Volume flexibility</td><td>[6]</td></tr><tr><td rowspan="3">Customer Management (CM)</td><td>CM1 Customer involvement in design</td><td>[1]</td></tr><tr><td>CM2 Continuous evaluation of customers' feedback</td><td>[1], [8]</td></tr><tr><td>CM3 Customer flexibility</td><td>[6]</td></tr><tr><td rowspan="8">Logistic Management (LM)</td><td>LM1 Postponement</td><td>[5], [6]</td></tr><tr><td>LM2 Continuous replenishment</td><td>[6]</td></tr><tr><td>LM3 Shorter planning period</td><td>[6]</td></tr><tr><td>LM4 Delivery flexibility</td><td>[6]</td></tr><tr><td>LM5 Use of 3PLs for transportation system</td><td>[6], [8]</td></tr><tr><td>LM6 Consignment inventory or vendor managed inventory</td><td>[6]</td></tr><tr><td>LM7 Effective logistic network design</td><td>[6]</td></tr><tr><td>LM8 Consolidated warehouses</td><td>[11]</td></tr><tr><td rowspan="7">Top Management Commitment (TMC)</td><td>TMC1 Responsibility and autonomy</td><td>[2]</td></tr><tr><td>TMC2 Cross-enterprise collaborative relationships and trust</td><td>[6]</td></tr><tr><td>TMC3 Employee training and education</td><td>[6]</td></tr><tr><td>TMC4 Good Decision Support System</td><td>[5]</td></tr><tr><td>TMC5 Holistic strategy for integrating system/ org. policy deployment</td><td>[6]</td></tr><tr><td>TMC6 Create vision and objectives to lean supply chain</td><td>[6]</td></tr><tr><td>TMC7 Nemawashi</td><td>[6]</td></tr><tr><td rowspan="6">Continuous Improvement (CI)</td><td>CI1 Job enlargement</td><td>[7]</td></tr><tr><td>CI2 Job enrichment</td><td>[7]</td></tr><tr><td>CI3 Six Sigma</td><td>[7]</td></tr><tr><td>CI4 Jidoka</td><td>[8]</td></tr><tr><td>CI5 TQM</td><td>[8]</td></tr><tr><td>CI6 Poka Yoke</td><td>[2]</td></tr></tbody></table>
<table><caption>**Table 2C.** Lean practices for SC uncertainty classified according to the 8-pillar model [6].</caption><thead><tr><th>Category</th><th>Practices</th><th>References</th></tr></thead><tbody><tr><td rowspan="2">Continuous Improvement (CI)</td><td>CI7 Cross functional team within the organization</td><td>[6]</td></tr><tr><td>CI8 Process performance measure</td><td>[2], [8], [11]</td></tr></tbody></table>

## 4 Linking LM practices with sources of uncertainty in SC

Once the main sources of uncertainty in SCs were defined together with the list of lean practices that can intervene to mitigate their effects or reduce their occurrences, a relationship map was built, as summarized in Table 3 and briefly described in the following.

**Product characteristic.** The adoption of design for X and concurrent engineering support cooperation between all parties involved in product design, help all participants achieve a better understanding of costs and time for product realization [2], while the implementation of postponement allows to produce variants only when more information is available. By implementing continuous replenishment and shortening the planning period, more frequent control is ensured, avoiding uncertainty in production volumes [5]. Moreover, the adoption of a short and integrated SC according to FIFO lane logics can ensure faster and more timely deliveries. Finally, postponement and modularisation allow production to be differentiated only when the customer's demand is better known [5].

**Manufacturing process.** Adoption of Total Productive Maintenance (TPM), for the development of preventive maintenance policies [8], implementation of streamlined re-layout of production lines [10], which allows to prosecute manufacturing processes on alternative lines in case of breakdowns, and introduction of job enlargement and enrichment enable flexibility in the redistribution of workforce. Lean six sigma is the recommended approach to deal with process variability, by controlling problems related to the standard deviation of processes [7]. Jidoka, which considers human involvement in automated processes, and Total Quality Management (TQM) represent viable ways to further eliminate wastes [8]. Moreover, the creation of a comfortable working environment and assignment of responsibilities to workers can help increase job satisfaction and, accordingly, reduce the risk of unproductivity. SDCA (standardize, do, check and act) practices are centered on the creation of stability [10]. Lastly, 5S is helpful in creating a safe and ergonomic work environment [2].

**Control chaos uncertainty.** One-piece flow principle and SMED practice, which lead to a reduction of lot sizes, allow to process smaller and more frequent orders [10]. The criticalities resulting from SC control systems, like wrong control rules and mismatch in the ICT system, can be mitigated by simplifying the information flow using information and communication technologies, such as enterprise resource planning.
ning (ERP), web interface devices for data exchange as extensive markup language (XML) and electronic data interchange (EDI) systems [5]. If synchronization is not possible, a good tool to transmit reliable information on effective consumption and to create an automated mechanism of coordination is represented by Kanban [2]. Meanwhile, sensor and radio frequency identification technologies represent additional tools that ensure transparent flows of information in the network [5]. Finally, the adoption of standard procedures simplifies the upstream work and allows the focal company to receive the information from SC partners in the required manner.

**Decision complexity.** Setting up cross-functional teams to define company objectives, defining a process-oriented system of goal setting and incentive allocation represent effective ways to avoid conflicting objectives [6]. Moreover, capacity constraints, for both production and logistic sectors, can be reduced by collaborating with the customer, to redefine service agreements, or with other support companies, through extra capacity ‘borrowing’ agreements. Administrative issues and decision policies can be dealt by redesigning decision procedures to eliminate unnecessary process steps.

**Organization/behavioral.** Implementing standard procedures, eliminating unnecessary decision process steps, and linking employee performance objectives with SC objectives can reduce the uncertainty due to political influence in the decision-making process. These practices, along with Nemawashi practice, which consists of a system of consensus building that first seeks informal approval of initiatives before the beginning of the formal process [2], may also reduce uncertainties associated with general behaviour where different predispositions can lead to disruption in the SC.

**End-customer demand.** Postponement and process flexibility in terms of production volume, may cope with seasonal demand variability, while maintaining close relationships with customers to anticipate their needs and earning their loyalty can help in retaining the current customer base, pending to learn from the market leader and adapt to the products offering [5].

**Demand amplification.** Demand signal processing may lead to unusual high stock levels in the upper region of the SC, which can be reduced by: elimination of functional interfaces to reduce time delays and information distortion (a technique is the VMI); application of time compression of both order information upstream and product transfer downstream; information sharing and tight coordination to enable synchronized planning; shorter planning period to avoid bullwhip effect; postponement to prevent over-reaction to short-term fluctuations in demand; ICT system to facilitate information sharing. Share of production plans and inventory with downstream SC partners can reduce rationing games to order more units than actually needed made from customers. Furthermore, order batching policy can be fought with proper information sharing or, better, by implementing a pull system and one-piece flow logic. In
the end, demand amplification due to price variations that lead to unexpectedly high demand can be solved through collaboration among SC partners along the whole chain.

**Supplier.** Developing and supporting plans with suppliers or streamlining the SC by vertical integration is necessary to grant that a specific level of service can be met, though this often requires the stipulation of long-term contracts. To deal with availability of supply, instead, agreements should consider guaranteed volume of supplied products. Close coordination to early intercept potential problems and work together on them to find a solution is key. To do so, a supplier ICT system to track the movement and usage of their materials can be used to improve volume flexibility [5]. Finally, selection of certified suppliers or helping suppliers in implementing Lean practices could be an option to get the right quality of supplied products [7].

**Parallel interaction.** Through reduction of partners involved in a SC it is possible to potentially reduce problems related to parallel interaction between businesses in each tier of the SC and other channels in the network, leading to increased responsiveness to customer orders. Furthermore, a good coordination among chain partners can also reduce the parallel interaction issue, as well as relying on ICT systems to exchange information provides suitable plans and delivery schedules [5].

**Order forecast horizon.** Increasing the frequency of deliveries to improve forecast accuracy or using computer assisted ordering to manage stock levels at retailers enable short information lead times [5]. Specifically, prove their effectiveness, the adoption of kanban to regulate the material flow dynamically, the use of milk run to ensure high frequency deliveries and the implementation of SMED to reduce batch size.

**Chain infrastructure and facilities.** Reduction of the number of suppliers to less spread the suppliers across the geographical area, building of production facilities closer to suppliers and customers to reduce shipping time, use of consolidated warehouses and outsourcing logistics, which enable a better schedule of delivery and reduction of transportation costs are valuable ways to manage the uncertainty related to chain infrastructure and facilities. ICT systems like EDI can provide dependable communication with suppliers and customers, while redesigning the chain infrastructure, by outsourcing transportation and distribution to a 3PL provider, enables effective delivery schedule and efficient operations [11].

**Environment.** Environment uncertainties, including changes in government regulations, can be mitigated by collaboration ruled by the Nemawashi principle. Even macroeconomic issues might press a company to change its plans: in this regard, the availability of production facilities in more countries can provide the necessary flexibility to temporarily switch production to other countries. Finally, to cope with com-
petitors' behaviour, collaboration can be created through horizontal mergers and acquisitions [5].

**Disruption/natural disasters.** Postponement, availability of production facilities in multiple locations, enabling customer flexibility with suitable incentives may increase customer satisfaction and sales during the disruption period [5].

<table><caption>**Table 3A.** Linking LM practices to address SC uncertainty</caption><thead><tr><th>Source of uncertainty in SC</th><th>Dimension</th><th>LM practices</th></tr></thead><tbody><tr><td>U1</td><td>Product specification</td><td>EW1; LM1</td></tr><tr><td>U1</td><td>Packaging characteristics</td><td>EW1</td></tr><tr><td>U1</td><td>Product lifecycle</td><td>LM2; LM3</td></tr><tr><td>U1</td><td>Product perishability</td><td>/</td></tr><tr><td>U1</td><td>Product variety offered</td><td>LM1</td></tr><tr><td>U2</td><td>Machine breakdowns</td><td>JITP1; JITP2; CI1</td></tr><tr><td>U2</td><td>Variable process yield and scrap-rates</td><td>CI3; CI4; CI5; EW1</td></tr><tr><td>U2</td><td>Changes in employee productivity</td><td>EW2; TMC1; TMC2; CI1; CI2</td></tr><tr><td>U2</td><td>Accidents</td><td>CI1; TMC3; EW3; JITP3</td></tr><tr><td>U3</td><td>Sales order is small compared with batch sizes</td><td>LM3; EW4; JITP4</td></tr><tr><td>U3</td><td>Chaos resulting from SC control systems</td><td>JITP5; TMC4; LM3</td></tr><tr><td>U3</td><td>Inaccurate or poor reports from SC partners</td><td>SM1; EW2; CI6</td></tr><tr><td>U4</td><td>Different goals across functional departments.</td><td>TMC5; TMC6; CI7</td></tr><tr><td>U4</td><td>Capacity constraints</td><td>TMC2; TMC4</td></tr><tr><td>U4</td><td>Uncertainty in long range strategic planning</td><td>/</td></tr><tr><td>U4</td><td>Administrative issues and decision policies</td><td>TMC5</td></tr><tr><td>U5</td><td>General behavior issue</td><td>CI8; TMC2; TMC3; MC4; TMC6; TMC7; EW2</td></tr><tr><td>U5</td><td>Internal politics</td><td>TMC7; EW2</td></tr><tr><td>U6</td><td>IT/IS system unavailability</td><td>/</td></tr><tr><td>U6</td><td>Data/information security issues that leads to uncertainties</td><td>/</td></tr><tr><td>U6</td><td>IT/IS system performance that leads to the uncertainty</td><td>/</td></tr><tr><td>U7</td><td>Seasonal demand variability</td><td>LM1; LM4; JITP6</td></tr><tr><td>U7</td><td>Changes in customer tastes</td><td>CM1; CM2</td></tr><tr><td>U7</td><td>Irregular or sporadic events</td><td>/</td></tr><tr><td>U8</td><td>Demand signal processing</td><td>JITP5; LM1; LM3; LM6; ITM1; ITM4; ITM5</td></tr><tr><td>U8</td><td>Rationing game</td><td>TMC2</td></tr></tbody></table>
<table><caption>**Table 3B.** Linking LM practices to address SC uncertainty</caption><thead><tr><td>Source of uncertainty in SC</td><td>Dimension</td><td>LM practices</td></tr></thead><tbody><tr><td>U8</td><td>Order batching policy</td><td>TMC2; JITP4; JITP5; ITM1; ITM3; ITM4</td></tr><tr><td>U8</td><td>Price variations</td><td>TMC2</td></tr><tr><td>U9</td><td>The timing of supply</td><td>SM1; SM2; SM3; SM4; SM5; ITM1; ITM5</td></tr><tr><td>U9</td><td>The quality of supplied product</td><td>TMC2; SM1; SM2; SM5</td></tr><tr><td>U9</td><td>The availability of supply</td><td>TMC2; SM3; SM5; ITM1; ITM4; ITM5</td></tr><tr><td>U10</td><td>General</td><td>SM3; SM4; TMC2; ITM1; ITM5</td></tr><tr><td>U11</td><td>General</td><td>LM3; JITP5; ITM1; ITM5</td></tr><tr><td>U12</td><td>The geographic areas</td><td>SM3; LM4; LM7; LM8; JITP6</td></tr><tr><td>U12</td><td>Communication</td><td>ITM1; ITM5</td></tr><tr><td>U12</td><td>Transportation infrastructure</td><td>LM7</td></tr><tr><td>U13</td><td>Political stability</td><td>/</td></tr><tr><td>U13</td><td>Government regulation</td><td>TMC2; TMC7</td></tr><tr><td>U13</td><td>Macroeconomic issues</td><td>JITP6; LM4</td></tr><tr><td>U13</td><td>Societal issues</td><td>/</td></tr><tr><td>U13</td><td>Competitor behavior</td><td>TMC2</td></tr><tr><td>U14</td><td>Natural disasters</td><td>LM1; JITP6; LM4; CM3; TMC2</td></tr></tbody></table>

## 5 Conclusion

Developed around a literature analysis and built upon two reference models, this paper contributes to consolidate the theoretical knowledge in the field of SCM, through a mapping of the LM practices suitable to address specific sources of uncertainty in SC. At the same time, it identifies those areas of uncertainty that cannot be effectively addressed through the use of lean thinking principles, providing important insights into areas of research still to be explored. The provided map is a valuable support tool for managers and consultants to assign priorities and efficiently develop LM action plans to address the distinctive sources of uncertainty in their SC. Being based on a literature study, the work requires further investigation to expand its theoretical view into a more practical perspective. In particular, experts' involvement and case studies emerge as necessary to complete the proposed map as well as to assess the actual effectiveness of adopted lean practices in relation to different industrial and organizational contexts.
References

1. Chopra, S., Meindl P.: Supply chain management: strategy, planning, and operation. 5th edn. Pearson, Boston (2013).

2. Pavanato, R.: The lean book. Come creare processi efficaci ed efficienti in ogni organizzazione. 1st edn., Guerini Next, goWare, Milan (2020).

3. Mohammaddust, F., Rezapour, S., Farahani, R. Z., Mofidfar, M., Hill, A.: Developing lean and responsive supply chains: A robust model for alternative risk mitigation strategies in supply chain designs. International Journal of Production Economics 183, 632-653 (2017).

4. Núñez-Merino, M., Maqueira-Marín, J. M., Moyano-Fuentes, J., Martínez-Jurado, P. J.: Information and digital technologies of Industry 4.0 and Lean supply chain management: a systematic literature review. International Journal of Production Research 58(16), 5034-5061 (2020).

5. Simangunsong, E., Hendry, L. C., Stevenson, M.: Supply-chain uncertainty: a review and theoretical foundation for future research. International Journal of Production Research 50(16), 4493-4523 (2012).

6. Jasti, N. V. K., Kodali, R.: A critical review of lean supply chain management frameworks: proposed framework. Production Planning & Control 26(13), 1051-1068 (2015).

7. Bicheno, J., Holweg, M.: The lean toolbox: A handbook for lean transformation. 5th edn. PICSIE books, Buckingham (2016).

8. Achieng, O. H., Githii, W., Ombati, O. T.: Lean supply chain and performance enablers at Homa lime company. American journal of industrial and business management 8(5), 1157-1171 (2018).

9. Awso, K., Habil, A., Shaaban, F.: The Role of some Activities of Lean Supply Chain Management (LSCM) in Achieving Logistics Excellence. Humanities Journal of University of Zakho 7(1), 142-160 (2019).

10. Coimbra, E. A.: Total Flow Management. Kaizen per l'eccellenza nella supply chain e oltre. 2nd edn. Guerini Next, Milan (2016).

11. Villarreal, B., Reyes, J. A. G., Ocañas, P., Martinez, F.: A lean transportation approach for reducing distribution cost: A case study. In: Proceedings of the 2017 International Symposium on Industrial Engineering and Operations Management (IEOM), pp. 1-9. IEOM Society International, Bristol (2017).