Logistics 4.0 in warehousing: a conceptual framework of influencing factors, benefits and barriers

Abstract

Purpose

In the last decade, the Industry 4.0 paradigm had started to rapidly expand to the logistics domain. However, Logistics 4.0 is still in an early adoption stage: some areas such as warehousing are still exploring its applicability, and the technological implementation of this paradigm can become fuzzy. This paper addresses this gap by examining the relationship among influencing factors, barriers, and benefits of Logistics 4.0 technologies in warehousing contexts.

Design/methodology/approach

Starting from a Systematic Literature Review (SLR) approach with 56 examined documents published in scientific journals or conference proceedings, a conceptual framework for Logistics 4.0 in warehousing is proposed. The framework encompasses multiple aspects related to the potential adopter’s decision-making process.

Findings

Influencing factors toward adoption, achievable benefits, and possible hurdles or criticalities have been extensively analyzed and structured into a consistent picture. Company’s digital awareness and readiness result in a major influencing factor, whereas barriers and criticalities are mostly technological, safety and security, and economic in nature. Warehousing process optimization is the key benefit identified.

Originality/value

This paper addresses a major gap since most of the research has focused on specific facets, or adopted the technology providers’ perspective, whereas little has been explored in warehousing from the adopters’ view. The main novelty and value lie in providing both academics and practitioners with a thorough view of multiple facets to be considered when approaching Logistics 4.0 in logistics facilities.

Citation

Perotti, S., Bastidas Santacruz, R.F., Bremer, P. and Beer, J.E. (2022), "Logistics 4.0 in warehousing: a conceptual framework of influencing factors, benefits and barriers", The International Journal of Logistics Management, Vol. 33 No. 5, pp. 193-220. https://doi.org/10.1108/IJLM-02-2022-0068

Introduction

Logistics is an ever-growing business that has gained increasing importance at a global level. Logistics market size was €5.6 trillion in 2018 and is projected to have a 4.6% compound annual growth rate (CAGR) until 2023 (Transport Intelligence, 2019). In Europe, logistics market size was €0.9 trillion in 2019 with a 2.4% CAGR forecasted for the 2018–2023 timespan (Transport Intelligence, 2019) and about 10.3 million citizens employed in 2018, thus making this industry highly relevant for the global economy (Eurostat, 2018). Within the logistics market, in-house warehousing and Third-Party Logistics (3PL) represent key activities with 30% of the total market value, and 38% in Europe (Transport Intelligence, 2019). Among logistics processes, warehousing is one of the most critical cost components (Rodrigue, 2020; Perotti et al., 2022), accounting for about 20% of logistics costs (Dhooma and Baker, 2012). Logistics facilities have been challenged by a substantial evolution over time (Baglio et al., 2019), as they have transformed from simple repositories for inventory into multi-functional logistics hubs (Baker, 2004; Onstein et al., 2019). This brought along challenges with higher requirements in terms of efficiency and service level fulfillment (Kembro et al., 2018).

In the past decade, also the manufacturing sector has started experiencing substantial changes, driven by factors such as sustainability concerns (Ghobakhloo, 2020). These changes have taken the manufacturing industry to experience a new transformation, for which Kagermann et al. (2011) have coined the term “Industry 4.0”, claiming to describe the fourth industrial revolution. In Industry 4.0, centralized control systems give way to decentralized decision-making. The aim of improving performances, and in some cases, the increase in complexity of business environments and more demanding requirements, are reshaping logistics and warehousing processes (Dev et al., 2021). To cope with this scenario, digitalization and the transition toward the Logistics 4.0 paradigm have become powerful means to compete in the market and help companies address the fragile trade-off between improved service levels and reasonable operating costs. Based on embedded sensors integrated with other technologies, objects such as machines, products, or orders, autonomously control themselves and are fully vertically integrated into the company’s information systems (Kagermann et al., 2011).

Since the term was coined in 2011, Industry 4.0 has become a dominant topic (Phuyal et al., 2020; Tang and Veelenturf, 2019). This is reflected by the growing number of publications, including an increasing number of logistics-related contributions since 2015 (Grzybowska and Awasthi, 2020). In this context, the exploration of Industry 4.0 technologies such as Autonomous Mobile Robots (Fragapane et al., 2021), Machine Learning, Artificial Intelligence (AI), and the Internet of Things (IoT) has also increased (Culot et al., 2020; Phuyal et al., 2020; Salamone et al., 2018). These technologies modify how the manufacturing industry operates, leading to a higher complexity of the manufacturing processes (Culot et al., 2020). In this context, some papers center their attention on the investigation of drivers and barriers to Industry 4.0 technologies adoption by considering different industrial perspectives. For instance, Tortorella et al. (2021) and Frederico et al. (2021) investigate the effect of Industry 4.0 technologies on supply chain resilience, showing a positive relationship between disruptive technology adoption and supply chain performance. Chauhan et al. (2021) focusing on companies in an emerging economy, propose to further explore this topic by investigating barriers as well as effects on companies’ performance. Also, Raj et al. (2020) study the barriers to Industry 4.0 adoption, considering both developed and developing countries. They suggest analyzing enabling factors for Industry 4.0. Lastly, Horváth and Szabó (2019) explore the barriers and driving forces of Industry 4.0 adoption from a general industry perspective while Stentoft et al. (2020) investigate the same topic from an SME perspective.

Logistics, directly affecting company’s productivity and service level as well as customer satisfaction, must also be able to adapt to the characteristics of the new Industry 4.0 manufacturing environment. Hence, it is questionable whether the current logistics systems and structures will be able to handle the increased complexity generated by Industry 4.0, more specifically without increasing costs or decreasing quality (Wang et al., 2020; Winkelhaus and Grosse, 2020). Companies need to align their logistics performance and development with the new requirements to support the vital link between manufacturers and customers that depends on logistics and warehousing operations (Winkelhaus and Grosse, 2020), resulting in the concept of “Logistics 4.0”. Logistics 4.0 is still a fuzzy term (Bag et al., 2020), and it is unclear which concepts it comprises (Oleśków-Szłapka and Stachowiak, 2019). For instance, a recent definition of Logistics 4.0 by Winkelhaus and Grosse (2020), refers to “the logistical system that enables the sustainable satisfaction of individualized customer demands without an increase in costs and supports this development in industry and trade using digital technologies”. Such definition, on the one hand, relates Logistics 4.0 to specific market factors (sustainability, individualized demand), while on the other hand is vague in the “digital technologies” required to implement them.

Warehouses play a key role in the Logistics 4.0 transition (Valchkov and Valchkova, 2018). Kumar et al. (2021) highlight relevant gaps related to Logistics 4.0 in warehouses and, more specifically, the need for frameworks to identify and address the challenges of its technological adoption. Indeed, most of the extant research mainly addresses two streams: either general benefits related to Logistics 4.0 adoption or the description of innovative technologies and solutions.

The first stream analyses possible benefits related to Logistics 4.0 in the warehousing context (Domański, 2019; Douaioui et al., 2018; Issaoui et al., 2021) and how operations could profit from Logistics 4.0 (Feng and Ye, 2021). For instance, Loureiro et al. (2020) concentrate on how Logistics 4.0 solutions help improve transaction costs and business coordination. Other researchers focus on the implications of Industry 4.0 for the logistics sector, emphasizing concepts such as digitalization and automation (Bag et al., 2020; Barreto et al., 2017; Schmidtke et al., 2018). Finally, Winkelhaus and Grosse (2020) investigate the possible benefits and challenges of Logistics 4.0 and provide a framework combining external triggers, underlying technological innovations, and impacts on human interactions and logistic tasks. Looking at the second stream, Cano et al. (2021) identify technologies framed into the Industry 4.0 concept that can be implemented also in logistics. Golpîra et al. (2021) investigate the areas of application, current development stage, and gaps of IoT in Logistics 4.0 transformation. Other authors discuss IoT applications in logistics from the perspectives of both, advantages and challenges that limit their adoption (Ding et al., 2021; Song et al., 2021; Tran-Dang et al., 2020). Chung (2021) focuses on the applications which various Industry 4.0 technologies could have in logistics processes. Intralogistics is explored by Fottner et al. (2021) who investigate the level of automation in intralogistics and the technologies that can enable it. Winkelhaus et al. (2021) analyze the socio-technological effects of Industry 4.0 on order picking systems.

Although the academic literature has started exploring how companies are approaching Logistics 4.0 adoption, a comprehensive conceptual framework addressing the adoption process of Logistics 4.0 in warehousing is missing. The aim of this paper is to offer a comprehensive conceptualization of Logistics 4.0 adoption in warehousing by embracing the adopters’ perspective and addressing the main influencing factors, achievable benefits as well as potential criticalities and barriers. This paper intends to address this research gap with a Systematic Literature Review (SLR) approach to provide robustness to the proposed conceptual framework. SLRs have been proved valuable as the initial step of defining a framework (Oleśków-Szłapka and Stachowiak, 2019; Winkelhaus and Grosse, 2020; Zoubek and Simon, 2021). Starting from the available literature on this topic, we categorize the relevant elements into a conceptual framework that can be used as a guideline by academics and practitioners.

The novelty and value of this paper lie in providing both academics and practitioners with a thorough view of the different facets to be considered when approaching the adoption of Logistics 4.0 solutions in logistics facilities. Specifically, influencing factors towards adoption, achievable benefits, and possible hurdles or criticalities will be extensively analyzed and structured into a consistent picture.

The remainder of the paper is structured as follows. The next section motivates and describes the SLR methodology adopted to ground the conceptual framework. Then, we present and discuss the results of our analysis. Finally, we draw conclusions and suggest future research directions.

Methodology

Systematic literature review (SLR) approach

As Logistics 4.0 in warehousing is a cutting-edge topic, an SLR approach is ideal to gather the most relevant information (Tranfield et al., 2003). The final goal of the SLR is to perform a critical analysis of research papers on Logistics 4.0 in warehousing to better comprehend the existing trends and research gaps (Carter and Rogers, 2008). Hence, the five-step methodology suggested by Denyer and Tranfield (2009) was adopted and hereinafter described.

Question formulation

To define the research questions in the context of the SLR (Phase 1), the CIMO (Context, Intervention, Mechanisms, Outcome) framework (Denyer and Tranfield, 2009) was used:

• 1 Context: The specification of individuals, relationships, institutional settings, or wider systems that are studied. Higher service levels requested by the market and the increasing logistics complexity require companies to develop new solutions for their logistics activities and, more specifically, for their warehouses.

• 2 Intervention: The events, actions, and activities that are studied. In this paper, the intervention is the application of Logistics 4.0 technologies.

• 3 Mechanisms: The mechanisms that explain the relationship between interventions, outcomes, and the circumstances under which these mechanisms are active. This should help companies find the most suitable solutions that leverage the benefits of Logistics 4.0 while mitigating risks and controlling costs.

• 4 Outcome: The effects of intervention, both intended and unintended ones. The aims associated with Logistics 4.0 in warehouses include, on the one hand, cost and time reduction for decision-making and for operations while maintaining service levels; on the other hand, providing higher service levels (e.g. by better utilizing the data emanating from ubiquitous sensors, higher quality of decision-making) while maintaining or optimizing costs (Winkelhaus and Grosse, 2020). The combination of these two objectives and their trade-offs is a constant challenge for managers and decision-makers.

Given this framework and the gaps which have emerged from the examination of the extant literature on the topic, three research questions were identified:

RQ1.

What are the main factors influencing a company’s level of readiness for the adoption of Logistics 4.0 in their warehouses?

RQ2.

What are the benefits that companies could achieve by implementing Logistics 4.0 solutions in their warehouses?

RQ3.

What are the main barriers and criticalities faced by companies when implementing Logistics 4.0 solutions in their warehouses?

The focus is set on influencing factors, benefits, and barriers with the purpose of specifically investigating the adoption process of Logistics 4.0 in warehouses, in line with previous logistics literature dealing with adoption processes (e.g. Li et al., 2020; Perotti et al., 2015).

Locating documents

Two main databases were used to locate the documents for the SLR (Phase 2): (1) Scopus as the largest repository of high-quality, peer-reviewed papers and, with the intention to broaden the literature sources, (2) Web of Science. A search string of keywords was built to address the influencing factors of the companies’ level of readiness, the achievable benefits, and the main barriers and criticalities faced by companies, consisting of two groups of keywords:

• 1 Group A comprehends keywords referring to Logistics 4.0, i.e.: “smart logistic*” OR “logistic* 4.0” OR “autonomous logistic*” OR “warehous* 4.0” OR “smart warehous*”.

• 2 Group B encompasses the specific aspects under investigation, i.e.: “adopt*” OR “demand*” OR “benefit*” OR “advantage*” OR “opportunit*” OR “barrier*” OR “criticalit*” OR “challeng*” OR “maturity” OR “readiness” OR “impact*” OR “factor*” OR “driver*”.

Paper selection and evaluation

328 documents were initially retrieved from Scopus and 201 from Web of Science, including duplicates. Merging and removing duplicates delivered 363 documents dated between October 2003 and April 2021. At this stage (Phase 3), a rigorous selection process, structured into screening, eligibility, and qualification, was applied using the inclusion and exclusion criteria reported in Table 1.

In the screening stage, phase, criteria 1 to 4 (Table 1) were considered to limit the results to those publications central to the purposes of this study. More specifically, criterion 1 evaluates the date of publication, due to the fact that the term Industry 4.0 has been first coined and used by Kagermann et al. (2011). Criterion 2 considers the attribution of the research, while criterion 3 ensures the quality of the papers, as scientific journals have a more rigorous review process than other document types (Colicchia et al., 2018) and conference proceedings cover emerging trends and challenges. Criterion 4 evaluates the language of publication. English is the language of choice as it is the most adopted and formally approved language for publications in the field of supply chain management (Colicchia et al., 2018). The screening phase delivered 274 papers out of 363 for the long list of papers.

In the eligibility stage, criteria 5 and 6 were applied. Both criteria are directly related to the main topics of the research questions. In this phase, the abstract, introduction, and conclusions of the papers were analyzed. This led to the exclusion of 185 papers, with 89 papers remaining in the sample.

Finally, in the qualification stage, all 89 papers were entirely read by two reviewers and carefully examined. As a result of this process, 33 papers have been excluded, because they were not specifically centered on the topics of interest. This led to a shortlist of 56 papers for critical in-depth analysis.

Review results

The resulting papers (step 5 of stage 1 in Figure 1) are reported in Appendix. They are listed in chronological order to highlight the developments that Logistics 4.0 has experienced over time (Melacini et al., 2018) and classified according to the following criteria:

• 1 Descriptive characteristics, i.e. general details such as article title, year of release, source title, and first author’s country.

• 2 Methodology adopted, namely literature reviews, conceptual works, analytical papers, empirical contributions (case studies/interviews and surveys), action research (implementation of a technology), and simulations. If a paper presented multiple methodologies, the prevailing one was considered for classification.

• 3 Research question addressed, by identifying the topics addressed i.e. (1) influencing factors regarding the company’s level of readiness for the adoption of Logistics 4.0 technologies assigned to RQ1, (2) benefits of the implementation of Logistics 4.0 solutions assigned to RQ2, and (3) barriers and criticalities that companies face when searching to implement Logistics 4.0 solutions assigned to RQ3. The results led to the development of a conceptual framework integrating three main dimensions associated with Logistics 4.0 adoption, namely motivations to adoption, benefits achieved, and barriers that emerged.

The following sections illustrate the descriptive analysis of the papers and describe the proposed conceptual framework as a result of the SLR study.

Descriptive analysis

Figure 2 shows the number of publications over time and by source. Initially, researchers gave priority to the development of Industry 4.0 concepts rather than Logistics 4.0. However, the number of publications per year related to Logistics 4.0 has steadily increased over time, and recently accelerated the pace, with 73% of the shortlisted papers published after 2018. The peak is in 2019, while 2020 recorded a small drop, possibly because of the COVID-19 pandemic. It is interesting to notice that the number of papers published in the first quarter of 2021 is almost the same as the sum of the two previous years, highlighting the growing interest of academics in Logistics 4.0 in warehouses.

Looking at the sources of the documents, a balance was found between papers published in scientific journals (34 papers, 48.6% of the sample) and conference proceedings (36 papers, 51.4%). The journals chiefly belong to the engineering and production management area, while a few are centered in other disciplines, such as policy management. As expected, most of the earliest papers were published in conference proceedings, indicating their ability to catch emerging trends.

Focusing on the first author’s affiliation country, most contributions (30) were Europe-based, followed by Asia (17), indicating strong interest from these regions.

Figure 3 illustrates the main research methodology used. Most of the early papers belong to the theoretical and conceptual domain whereas more recently the number of empirical contributions has increased substantially. Action research only started to appear in the last years. This shows that Logistics 4.0 in warehousing is attracting rising attention and it is likely going to become a well-developed research topic. Following a similar methodology as some documents found in the literature (Golpîra et al., 2021; Kumar et al., 2021; Winkelhaus et al., 2021), in our study, all the research methodologies (theoretical, conceptual, and empirical or action research) are considered relevant. Since the results of some methodologies can complement others, this helps to get a clearer idea of current Logistics 4.0 adoption as well as of future trends.

Finally, as far as the research question(s) being addressed, topics connected to RQ2 (35 related papers) and RQ3 (25 results) are prevailing, thus indicating that benefits from adoption as well as related barriers and criticalities have already started to be analyzed. Conversely, it seems that so far very little has been explored regarding the influencing factors on the company level for the readiness for adopting Logistics 4.0 in their warehouses.

Conceptual framework of logistics 4.0 adoption in warehousing

Starting from the in-depth analysis of the SLR papers and the RQs considered for our study, a comprehensive conceptual framework related to Logistics 4.0 adoption in warehouses was developed. The framework (Figure 4) specifically encompasses three interconnected dimensions that are strictly associated with the Logistics 4.0 adoption process in warehouses:

• 1 Influencing factors, referring to the elements that might influence the company’s decision to adopt Logistics 4.0 solutions in their warehouses. Companies are chiefly affected by their warehouse management and operation, their digital awareness and readiness, their employees’ educational level, and governmental support and policies.

• 2 Benefits, indicating the advantages that Logistics 4.0 solutions applied in warehouses might offer. In terms of operations, these benefits are process optimization, transaction cost reduction, flexibility increase, traceability and visibility enhancement, human error reduction, human resource management and safety enhancement, and sustainability improvement. Additionally, from the customer perspective, the main benefits are increased customer loyalty and satisfaction.

• 3 Barriers and criticalities, dealing with all the challenges that companies might face when embracing Logistics 4.0 in warehousing. Several types of hurdles can be identified: strategic (e.g. no standardized implementations exist), economic (e.g. high implementation costs), technological (e.g. obsolete infrastructures), cultural (e.g. companies are not ready for advanced technologies), and safety and security related (e.g. risk of cyber-attacks).

In the framework, the elements that compose each of the three dimensions are organized by their relative importance in the examined literature i.e. the frequency with which each aspect was a relevant point of discussion. This gives a clear view of the most and least relevant factors from the academic perspective. Additionally, the framework shows how each of the influencing factors is related to specific barriers and criticalities, giving an insight into how these two dimensions are interrelated and affected by one another. Finally, the benefits that Logistics 4.0 adopters could obtain are shown and organized from most to least investigated in the literature, which is relevant as Logistics 4.0 adopters can relate the specific requirements in their warehouses with the benefits identified by academics.

Our approach is in line with typical technology acceptance models (TAMs). In its basic form (Figure 4) it is similar to the original TAM developed by Davis et al. (1989): The influencing factors resemble the external variables while benefits correspond to perceived usefulness, and barriers and criticalities indicate the obstacles to the ease of use. We did not follow TAM2 (Venkatesh and Davis, 2000), as we consider its main extensions compared to the original TAM, namely a more differentiated approach to external factors like social influence and cognitive processes, not relevant for our study. For the same reason, we have not used the unified theory of acceptance and use of technology (UTAUT) model suggested by Venkatesh et al. (2003), as we think that factors like gender and age do not affect Logistics 4.0 adoption or moderate key influencing factors substantially. Our approach is in accordance with general concerns that the more elaborated models suggest additional moderators without explaining the reasons behind the proposed interaction effects (Bagozzi, 2008). Following Bagozzi (2008), we believe that the parsimony of the framework, its simple set-up, is strength rather than weakness and fits well into the managerial decision-making context.

Table 2 reports a detailed analysis of the framework elements and related references. In the subsequent paragraphs, each element is carefully described, as well as its related factors.

Influencing factors (RQ1)

Warehouse management and operation, the company’s digital awareness and readiness, employees’ educational level, and governmental support and policies have emerged as the main influencing aspects, thus addressing RQ1.

First, the warehouse management and operations currently in place represent a major influencing factor. From this viewpoint, companies need to carefully consider their as-is configuration first – e.g. financial as well as operational factors, product characteristics as well as supply chain structure – together with the related performance and criticalities before deciding whether and how to embrace the digital transition that Logistics 4.0 implies (Boonsothonsatit et al., 2020). For example, Zoubek et al. (2021) propose a methodology to address the rationalization of a warehouse system by offering a range of 4.0 scenarios with different digital solutions that can be evaluated and selected based on the specific warehouse setting and requirements.

The second key influencing factor refers to the company’s digital awareness and readiness (Zouari et al., 2020). The lack of technological culture is one of the biggest hurdles the logistics industry is facing, and the company’s maturity and attitude toward the digital landscape affect the implementation of Logistics 4.0 in warehouses. As companies are not always fully aware of the digital options and how such solutions might impact their business, their perception might be biased and, consequently, implementation of Logistics 4.0 technologies in warehouses might be perceived as risky (Barczak et al., 2019). Some researchers have started analyzing the company’s technological maturity level, e.g. by means of frameworks such as the one proposed by Mahroof (2019) with technology, organization, and environment as the main pillars or five levels (Stachowiak et al., 2019) ranging from “ignoring” (i.e. full unawareness of Logistics 4.0) to “integrated” (i.e. companies that have effectively implemented fully integrated Logistics 4.0 solutions). Also, more general characteristics such as automation level or capability to manage data are included (Zoubek and Simon, 2021). Finally, Modrak et al. (2019) propose a self-assessment model for smart logistics maturity, in which one of the five clusters is entirely focused on warehouses.

As far as employees’ educational level is concerned, Logistics 4.0 requires at its base a certain level of digital education. The development of human skills is one of the main requirements to maintain competitiveness (Krishnan and Wahab, 2019; Wrobel-Lachowska et al., 2018), and employees must be educated in a way that permits them to stay in line with cutting-edge trends. When approaching the 4.0 paradigm, training in technological knowledge and software/hardware usage is required (Woschank and Pacher, 2020a) and a combination of scientific, industry-specific, and firm-related capabilities should be promoted (Wrobel-Lachowska et al., 2018). Some scholars have investigated the learning process and suggested specific methods in the context of logistics engineering education, seeking to guarantee comprehensive training, characterized by both a theoretical and practical approach (Nazir et al., 2019; Woschank and Pacher, 2020b). Anecdotal evidence from a large number of planning and consulting projects in the warehousing industry conducted by the authors indicates that, traditionally, warehouses have not been considered work environments that require any significant level of technological education on the operational level, suggesting that a high employee’s educational level, if present, would likely rather be qualified as an influencing factor (e.g. higher technology awareness and understanding of the benefits potentially achievable) than a barrier to implementation.

Finally, policies used by different countries to promote the transition to the 4.0 paradigm and their governments’ intervention can significantly affect the implementation of Logistics 4.0 in warehouses. For instance, actions such as (1) cost reductions in the import of external technology or (2) the promotion of international exchange of knowledge can support the local development of technologies and competence (Krishnan and Wahab, 2019). Moreover, the government could financially support companies through incentives and strategic programs. Also, the collaboration among companies, academia, and the public sector might be fundamental for accelerated Logistics 4.0 implementation by increasing the adopters’ readiness level (Stachowiak et al., 2019).

Benefits (RQ2)

The main advantages emerging from Logistics 4.0 implementation refer to warehousing process optimization, transaction costs reduction, flexibility increase, traceability and visibility enhancement, human error reduction, human resource management, safety enhancement, sustainability improvement, and increased customer loyalty and satisfaction.

The possibility to improve process performance through the implementation of Logistics 4.0 technologies in warehouses is a widely addressed topic, especially from a conceptual perspective (Barreto et al., 2017; Correa et al., 2020; Issaoui et al., 2021; Kuczyńska-Chałada et al., 2018; Nantee and Sureeyatanapas, 2021; Oleśków-Szłapka and Stachowiak, 2019; Song et al., 2021; Wen et al., 2018; Winkelhaus and Grosse, 2020; Woschank and Zsifkovits, 2021).

For instance, Wang (2016) suggests potential cost savings and a reduction in inventory costs. Some other scholars offer empirical studies to corroborate their views (Affia and Aamer, 2021; Domański, 2019; Gialos and Zeimpekis, 2020; Hamdy et al., 2018; Kekana et al., 2020; Krishnan and Wahab, 2019; Lee et al., 2018; Plakas et al., 2020; Zhang et al., 2021). However, it is necessary to critically assess the benefits directly associated with the technologies mentioned in the Logistics 4.0 literature to clearly point out whether and how they add something new to the technologies already adopted in warehouses, i.e. it is necessary to carve out what Logistics 4.0 adds to standard automation in warehouses.

One of the key factors that must be addressed in order to optimize logistics and warehousing processes is increasing their efficiency (Domański, 2019; Krishnan and Wahab, 2019; Zhang et al., 2021). For instance, this can be obtained with the implementation of technologies such as IoT-based solutions which offer real-time data visibility (Hofmann et al., 2019; Lee et al., 2018), Augmented Reality, and Smart Glasses which improve operations performance (Plakas et al., 2020), or AI tools to automate the recognition of objects and, through Machine Learning, to infer insights valuable for decision-making (Wen et al., 2018).

Transaction cost reduction has been also highlighted as a benefit of Logistics 4.0 implementation. Transaction costs are defined as “the consumption of economic resources resulting from adapting, structuring, and monitoring the interactions between the different agents, ensuring compliance with contracts” (Loureiro et al., 2020). According to these authors, the implementation of Logistics 4.0 solutions can reduce transaction costs in warehousing by providing timely information supporting the decision-making process and improving the relationship with other stakeholders. One example is the implementation of smart sensors to locate items inside the warehouse. Transmitting the information to other partners of the supply chain, optimizing resources assignment, and reducing the costs associated with the process have emerged as the foremost achievements.

The implementation of Logistics 4.0 in warehouses might increase flexibility and/or responsiveness (Barreto et al., 2017; Karunarathna et al., 2019; Oleśków-Szłapka and Stachowiak, 2019; Song et al., 2021). Several authors suggest equipping existing automation technology such as automated guided vehicles (AGVs) with smart features to increase flexibility. For instance, Mehami et al. (2018) combine AGVs with RFID technology to allow RFID-tagged items to determine the path of the AGV at runtime. The implementation of robots in the warehousing context has been a topic of discussion for its possibilities to increase efficiency and reduce repetitive tasks for humans (Raji et al., 2021). To this end, Lourenco et al. (2017) prototyped an autonomous mobile robot that can handle transportation from manufacturing supermarkets to assembly stations while avoiding obstacles, as it is intended to operate in a dynamic environment together with other autonomous robots and human operators. The approach of adding autonomous features to existing technologies is also in line with the maturity model proposed by Zoubek and Simon (2021) related to Logistics 4.0 in internal processes.

However, although many scholars support the view that Logistics 4.0 might offer ample opportunities for flexibility increase, this is not endorsed by the entire academic community (Nantee and Sureeyatanapas, 2021). For instance, Cimini et al. (2021) found that the introduction of Logistics 4.0 in the picking process did not prove to be the best option in terms of flexibility, thus preferring humans to robots.

A major benefit refers to traceability and visibility enhancement, intended as the availability of data, the visibility of logistics objects and actors, and the transparency of processes within the value chain. Thanks to the implementation of Logistics 4.0, information flows can be synchronized with product flows (Barreto et al., 2017; Douaioui et al., 2018; Oleśków-Szłapka and Stachowiak, 2019; Wang, 2016). For instance, as the IoT enables device connectivity, the visibility of logistics activities and sharing capabilities in warehouses can be considerably improved (Winkelhaus and Grosse, 2020; Nantee and Sureeyatanapas, 2021).

To guarantee the visibility and traceability of logistics objects, it is necessary to be able to precisely localize them inside and outside warehouses. Liu et al. (2018) discuss the state-of-the-art technologies available to perform this task. The most common technologies are GPS, Bluetooth, and RFID. For several years, RFID has been considered to have a possible positive effect on visibility and efficiency in warehousing (Vijayaraman and Osyk, 2006). Nevertheless, the specific drawbacks of each technology must be considered. While GPS has high accuracy for outdoor localization, it cannot be used indoors. RFID help localize objects indoors with a high degree of accuracy, while it requires an extensive infrastructure that can have limitations in large-scale outdoor applications. In addition, in some cases, the calculation of its ROI can be fuzzy (Vijayaraman and Osyk, 2006). Therefore, each warehouse case must be assessed based on its specific needs. From a more practical perspective, Affia and Aamer (2021) propose a roadmap to design and apply an IoT-based smart warehouse infrastructure allowing data recording, tracking, reporting, and immediate distribution to all authorized stakeholders. Despite the increase in visibility and traceability, it is noteworthy to say that these shared data could represent a challenge for digital security.

The reduction in error rates and associated risks are two of the main benefits related to the implementation of Logistics 4.0 in warehouses. Numerous studies have tackled this issue, either theoretically (Karunarathna et al., 2019; Nantee and Sureeyatanapas, 2021; Oleśków-Szłapka and Stachowiak, 2019; Plakas et al., 2020; Wang, 2016; Zoubek et al., 2021; Zoubek and Simon, 2021) or empirically (Lee et al., 2018). For instance, the implementation of cyber-physical system (CPS) which combines virtual and physical worlds through smart objects can reduce errors during the process (Zoubek et al., 2021). In this context, AR picking, and RFID solutions could mitigate the risk of human error (Karunarathna et al., 2019; Nantee and Sureeyatanapas, 2021; Plakas et al., 2020; Winkelhaus and Grosse, 2020).

Another key benefit refers to human resource management and safety enhancement. Employees are expected to work in a safe environment, allowing them to perform their tasks and improve their skills while feeling safe and aligned with the company’s mission. Logistics 4.0 technologies can help minimize stressful and repetitive human tasks and reduce the risk of injuries, fatigue, and mental stress. For instance, Nantee and Sureeyatanapas (2021) highlighted that employees perceived increased ease in their daily operations and the development enhancement of their analytical and computing skills. A general improvement in operational efficiency in the warehouse has been also highlighted (Cimini et al., 2019, 2021; Halawa et al., 2020).

Sustainability improvements have also been identified (Calza et al., 2020), e.g. poor energy management (Buntak et al., 2019). The reduction of costs generated by inefficiencies would make available additional resources for environmental and social improvements. Some studies suggest that Logistics 4.0 technologies in long-term and high-scale operations have the potential to bring sustainable advantages in terms of increased efficiency and reduced waste and emissions (Krishnan and Wahab, 2019; Nantee and Sureeyatanapas, 2021).

Additional advantages are increased customer satisfaction and the possibility of improved customer loyalty, thus reducing the churn rate (Kekana et al., 2020). In this sense, four dimensions have appeared highly significant: (1) reliability of the delivery, (2) process visibility, (3) empathy for the customer, and (4) tangibility of the company. Logistics 4.0 can leverage these domains to build a long-term relationship between a company and its customers. From this perspective, Kekana et al. (2020) assessed the relationship between the warehousing style of an organization and both customer satisfaction and loyalty. It was found that IoT and RFID were the main levers enhancing logistics performance in the warehouse. In other cases, it was pointed out that Logistics 4.0-automated warehouses can increase customer satisfaction by improving shipping and information accuracy, product customization, and reducing lead time (Nantee and Sureeyatanapas, 2021). These results are also supported by other sources which highlight that improved visibility, achieved by means of technologies such as IoT, blockchain, and cloud platforms, is another key dimension that leads to higher customer satisfaction (Markov and Vitliemov, 2020).

Barriers and criticalities (RQ3)

Different types of hurdles have been identified for Logistics 4.0 adoption in warehouses i.e. strategic, economic, technological, cultural, and safety- and security-related obstacles.

The first obstacle to Logistics 4.0 implementation involves strategic considerations. Implementation of 4.0 technologies in warehouses cannot be standardized but needs to be tailored to the specific case (Jung and Kim, 2015). The design of a Logistics 4.0 warehouse needs to be adapted to the specific company’s operating environment (Affia and Aamer, 2021), while the company’s targets and priorities must be carefully taken into account (Wen et al., 2018).

Looking at the economic perspective, the costs associated with the investment for warehousing 4.0 represent another barrier. These costs, of course, depend on the technologies being implemented. When a complete warehouse re-design is required, the investment tends to be high (Cyplik et al., 2019; Markov and Vitliemov, 2020; Oleśków-Szłapka and Stachowiak, 2019; Zoubek et al., 2021), thus preventing companies from easily embracing the Logistics 4.0 paradigm. In some cases, a step-by-step implementation strategy is preferred (Phuyal et al., 2020; Schmidtke et al., 2018). The investment costs to be considered include numerous factors, such as equipment, deployment, and training costs (Tran-Dang et al., 2020). To cope with these factors, a detailed cost and Return on Investment analysis should be performed by companies before deciding on implementation of Logistics 4.0 technologies (Verma et al., 2020). Companies are sometimes reluctant since they find it difficult to quantify the beneficial effect of Logistics 4.0 implementation in advance. This involves not only direct but also indirect effects that are hardly measurable (Poenicke et al., 2019).

Technological barriers exist, too (Cyplik et al., 2019; Verma et al., 2020; Zoubek et al., 2021). They include the lack of reliable infrastructures or difficulties of integration with the legacy systems running within the warehouse. For instance, the use of cutting-edge engineering applications such as multi-robot collaboration requires companies to develop algorithms that must be supported by robust middleware systems and programming models (Liu et al., 2018). In general, as Logistics 4.0 is still in its infancy, immature technologies together with unstandardized function modules are also identified as key barriers to Logistics 4.0 adoption (Feng and Ye, 2021). Overall, suitable digital infrastructure has been identified as a basic requirement for implementing Logistics 4.0 applications (Schmidtke et al., 2018).

Furthermore, cultural hurdles have been highlighted. Logistics 4.0 implementation requires the integration of a broad range of technologies, and companies require additional knowledge and skills that can be achieved through investments and training (Correa et al., 2020). However, many companies tend to act as routine-blinded adopters as their digital maturity level is still low, and also resistance to change might be another hurdle to adoption (Correa et al., 2020).

Also, the lack of specific skills to operate the components of a Logistics 4.0 warehouse is considered an obstacle (Affia and Aamer, 2021; Zoubek et al., 2021). Since collaboration with smart equipment and technologies will be increasingly common in future warehouses, the education of specialized employees will become a key requirement (Schmidtke et al., 2018; Verma et al., 2020). Such a shift in terms of technical skills must be accompanied by a change of mentality in the companies themselves (Mahroof, 2019).

Finally, safety and security issues represent another important barrier. Making logistics and warehousing systems secure is vital for technology adopters. This involves several concerns related to cyber-attacks (Hamdy et al., 2018; Jamai et al., 2020; Markov and Vitliemov, 2020). The higher the number of devices connected to the IoT network, the higher the possibility of security and privacy issues (Song et al., 2021). As an example, privacy violations related to tracking the locations of certain items could compromise a company’s competitive advantages (Ding et al., 2021). For this reason, companies must consider security and privacy urgent requirements (Verma et al., 2020; Zhu et al., 2020). In this context, blockchain-based systems are often proposed. However, blockchains are not able to avoid and defuse cyber-attacks (Liu et al., 2018) but are centered on ensuring that information cannot be modified ex-post (Tan and Ngan, 2020). Besides, additional physical safety challenges have been raised for automated devices, such as robots, drones, or AGVs, that can cause harm for operators (Trab et al., 2017).

Discussion and conclusions

Warehouses are crucial components of logistics networks, and their strategic role has been increasingly recognized by both researchers and practitioners. Logistics 4.0 in warehousing involves the introduction of Industry 4.0 technologies and practices within warehouses with the intention to enhance operations and service levels. In recent years, this field has gained growing interest among academics and a rising number of studies emphasize the relevance of this topic in the logistics domain.

Looking at RQ1 (What are the main factors influencing a company’s level of readiness for the adoption of Logistics 4.0 in their warehouses?), four main clusters of factors have been identified, namely warehouse setting and management, company’s digital awareness and readiness, employees’ educational level, and governmental support and policies. Specifically, warehouse setting and requirements (e.g. goods flows to be managed, products to be stored, service level, expected lead times) as well as the company’s digital awareness (Zouari et al., 2020) are critical elements impacting Logistics 4.0 adoption in warehousing.

As for RQ2 (What are the benefits that companies could achieve by implementing Logistics 4.0 solutions in their warehouses?), the literature reviewed mentions a variety of possible benefits that Logistics 4.0 technologies in warehousing can bring about. However, the lack of empirically validated data does not allow one to state with certainty which (or even if) benefits can be achieved in practice. In some cases, benefits claimed by suppliers of technology associated with Logistics 4.0 for warehouses were uncritically repeated (e.g. Mahroof, 2019). In other cases, it is impossible to tell apart whether proclaimed improvements can be attributed to the introduction of technology or simply to the review and reorganization of warehouse processes that typically accompany the introduction of technology. This challenge is further exacerbated by the finding that the technologies associated with the label Logistics 4.0 are highly inconsistent among the authors of the literature reviewed. Indeed, some authors point out that technologies that have existed in warehouses for decades, preceding the concept of Industry 4.0 and Logistics 4.0, e.g. Automated Storage and Retrieval Systems (Domański, 2019) RFID, and AGV, are placed under the 4.0 umbrella.

With respect to RQ3 (What are the main barriers and criticalities faced by companies when implementing Logistics 4.0 solutions in their warehouses?), strategic, economic, technological, cultural, and safety and security-related barriers and criticalities have been identified. Particularly, the coverage of economic aspects, arguably the most important decision-making criterion for technology adoption, has been weak. Generally speaking, economics suggest technology adoption when the capital invested will lead to overall cost savings within a defined period of time. Since tangible benefits from the adoption of Logistics 4.0 technology in warehouse applications were found to be only vaguely defined, and with little reliable quantitative underpinning, it is not surprising that the discussion of economic barriers has remained equally vague. Also, the organizational structure has received little attention in the context of economic considerations, though it can be speculated that (for example in the case of third-party logistics providers) the interplay between independently managed warehouses (as profit centers) and headquarters (which include marketing and sales functions) would influence the adoption of Logistics 4.0 technologies.

Both academic and practical implications can be identified. From an academic perspective, this paper, by means of an SLR approach, offers a conceptual framework for Logistics 4.0 adoption in warehousing from the technology adopter’s perspective. It provides a clear outlook on the motivations, benefits, and challenges the implementation of Logistics 4.0 in warehousing could entail. From a practical viewpoint, the framework intends to ease the understanding of the technological possibilities that Logistics 4.0 could bring, with the final objective to better understand the specific technology adoption process. It also highlights the importance of analyzing the individual requirements for each specific company and application. The overall aim is to promote knowledge on the topic of Logistics 4.0 in the warehousing domain, stimulating a higher awareness of the topic, and fostering the adoption process of such applications. More practically, it helps organizations understand the breadth of technologies associated with Logistics 4.0, as well as both, challenges and benefits that can reasonably be expected, albeit predominantly qualitatively rather than quantitatively.

A more sober implication for academia results from the finding that the use of the term Logistics 4.0 in the warehousing concepts with its synonyms (e.g. “smart”) and related concepts (e.g. “IoT”) in the literature reviewed seems sometimes ambiguous, ranging from pure automation to decades-old identification technology to picking support devices (e.g. pick-by-voice) to more recent digital technologies such as artificial intelligence. Considering the breadth of its use, it can be questioned whether the term Logistics 4.0 is useful at all. Since academics should strive for conceptual and terminological clarity, the ambiguity of the term and its related concepts is creating serious concerns for use outside of corporate marketing departments. Should researchers decide to continue using the term, it is strongly recommended to focus efforts on some of the research lines pointed out in the section “Research gaps and suggested future research directions”.

Lastly, the study’s limitations must be acknowledged. In particular, the main limitation lies in the potential omission of relevant contributions from the review as the process of selection considered only journal and conference papers. Although the keyword structure was designed through several trials to ensure the most effective and feasible research space, it cannot be excluded that other papers dealing with this subject exist under different labels. Several papers discussed the same terms with a different understanding or definition of them. Further research is, therefore, recommended to encourage a higher degree of standardization. Moreover, it can be assumed that the more generic term “Industry 4.0” is sometimes used when Logistics 4.0 would apply as a more specific label. Nevertheless, because of the methodology adopted, it is believed that this analysis provides an adequate representation of the state of the art of literature related to influencing factors, benefits, and barriers dealing with Logistics 4.0 in warehousing. The study should be further supplemented with empirical research, including challenging the proposed framework.

Research gaps and suggested future research directions

The proposed framework has also revealed the gaps and limitations of the revised literature, therefore, highlighting streams for future research. In the following, six research lines (RLs) for future investigation are offered and discussed.

RL1.

Develop strong conceptualization and taxonomies clarifying 4.0 technologies for warehousing.

A lack of clarity has emerged concerning whether a certain technology is belongs to the Logistics 4.0 domain, and it seems that the boundaries between Logistics 4.0 and state-of-the-art automation are still fuzzy. This is even more critical for warehousing, as it seems even less in focus, with no standardized taxonomy or classifications. There is a high variety of terms and definitions that might cause confusion or even hinder technology implementation. Indeed, practitioners and potential adopters might be put off by standard technologies that are sometimes sold under the Logistics 4.0 label. Further efforts should be promoted to make Logistics 4.0 concepts and solutions clearer to practitioners.

RL2.

Foster empirical research in the field of Logistics 4.0 adoption in warehousing.

A major lack of empirical investigation has been identified in the warehousing arena. Particularly, the focus was often placed on specific companies or application environments rather than larger samples or cross-case analyses. This would be beneficial both, to promote higher generalizability of results and to provide a clearer view of the company’s current level of Logistics 4.0 adoption in their warehouses, including the types of solutions mostly implemented. Empirical investigation can be also valuable from two additional perspectives: On the one hand, to validate the numerous conceptual and theoretical ideas that have started to emerge. On the other hand, to better investigate the integration among different Logistics 4.0 technologies in warehousing. Although the relationship among Logistics 4.0 technologies in warehousing has started to be discussed in some papers, none of them has provided empirical results to corroborate their conceptual contributions. Moreover, where the benefits of Logistics 4.0 technology adoption are described, it often remains unclear whether these benefits are due to the new technology or can be explained by process adaptions that are a necessary condition for technology implementation and would have led to improved performance even without additional technology.

RL3.

Improve the examination of the relationship between Logistics 4.0 application and specific warehousing activities.

A need has emerged for deep dive into the decision-making process related to Logistics 4.0 adoption with a more detailed focus on specific warehousing processes and activities (e.g. receiving, storage, picking, and shipping). So far, the analysis of Logistics 4.0 in warehouses has been mostly carried out without a comprehensive perspective on the entire range of operations. Only specific warehousing processes have started to be examined under the 4.0 lenses, such as picking operations, but other relevant activities such as inbound logistics, storage, or inventory management are still underrepresented.

RL4.

Promote further investigation on the role of governmental support in influencing Logistics 4.0 investments at logistics sites.

Looking at the influencing factors, the relationship between government support and adoption of Logistics 4.0 in warehouses, which in some countries is relevant and could boost adoption, is still little investigated. Although governmental support has been stated to be influential in companies’ decisions to invest in Logistics 4.0 technologies, no papers have been found that clearly analyze such a relationship. The literature discusses this issue only in general terms and by referring to frameworks not specifically designed for Logistics 4.0.

RL5.

Encourage further cost-benefit trade-off analyses of Logistics 4.0 in warehouses.

The expected cost-benefit ratio related to the implementation of Logistics 4.0 in warehousing is another promising topic that deserves more investigation. A common barrier that prevents companies from implementing Logistics 4.0 solutions lies in difficulties trading off the investment costs against both, tangible and intangible operational benefits in warehouses. As economic considerations are a main driver of technology adoption, one of the practical challenges is the distinction between benefits derived from adopting one technology (that may or may not be associated with Logistics 4.0, such as AGVs) and the adoption of a combination of different technologies at once (e.g. AGVs in combination with advanced control and identification mechanisms that would qualify as IoT). Further studies are encouraged in this direction.

RL6.

Develop quantitative assessment research of the sustainability implications of Logistics 4.0 in warehousing.

As a final remark, quantitative assessment of sustainability-related impacts of Logistics 4.0 in warehousing has emerged as a promising research arena. According to the SLR, one contribution has been specifically found that assesses the impact of 4.0 in warehousing through the lenses of the Triple Bottom Line (TBL) framework (Nantee and Sureeyatanapas, 2021). However, in their assessment, only a qualitative approach centered on a single case was included, leaving ample room for further contributions in this field; additional quantitative-based studies, models, or simulations are recommended.

Figures

Figure 1

Methodological framework of the study

Figure 2

Examined publications over time

Figure 3

Publications by methodology over time

Figure 4

Conceptual framework for logistics 4.0 adoption in warehousing: influencing factors, benefits, and barriers

Table 1

Inclusion and exclusion criteria

No.	Inclusion criteria	Exclusion criteria
1	Published after 2010	Published before or during 2010
2	Author name(s) available	Author name(s) not available
3	Published in a scientific journal or as a conference paper	Other publications
4	Published in English	Published in other languages
5	Logistics 4.0 in warehouses	Logistics 4.0 related to transportation and distribution (outbound logistics)
6	Deal with or mention the demand side (adopters’ perspective)	Focus on the supply side (providers’ perspective)

Table 2

Detailed analysis of framework elements and related references

Framework elements	Factors	No. Papers	Main references
Influencing factors (RQ1)	Warehouse setting and management	4	Affia and Aamer (2021), Boonsothonsatit et al. (2020), Krishnan and Wahab (2019), Zoubek et al. (2021)
	Company’s digital awareness and readiness	6	Barczak et al. (2019), Mahroof (2019), Modrak et al. (2019), Oleśków-Szłapka and Stachowiak (2019), Stachowiak et al. (2019), Zoubek and Simon (2021)
	Employees’ educational level	4	Nazir et al. (2019), Woschank and Pacher (2020a, b), Wrobel-Lachowska et al. (2018)
	Governmental support and policies	3	Feng and Ye (2021), Krishnan and Wahab (2019), Oleśków-Szłapka and Stachowiak (2019)
Benefits (RQ2)	Process optimization	20	Affia and Aamer (2021), Barreto et al. (2017), Correa et al. (2020), Domański (2019), Gialos and Zeimpekis (2020), Hamdy et al. (2018), Issaoui et al. (2021), Kekana et al. (2020), Krishnan and Wahab (2019), Kuczyńska-Chałada et al. (2018), Lee et al. (2018), Nantee and Sureeyatanapas (2021), Oleśków-Szłapka and Stachowiak (2019), Plakas et al. (2020), Song et al. (2021), Wang (2016), Wen et al. (2018), Winkelhaus and Grosse (2020), Woschank and Zsifkovits (2021), Zhang et al. (2021)
	Transaction costs reduction	1	Loureiro et al. (2020)
	Flexibility increase	12	Agalianos et al. (2020), Barreto et al. (2017), Cimini et al. (2021), Karunarathna et al. (2019), Lourenco et al. (2017), Nantee and Sureeyatanapas (2021), Oleśków-Szłapka and Stachowiak (2019), Song et al. (2021), Woschank and Zsifkovits (2021), Zhang et al. (2021), Zoubek et al. (2021)
	Traceability and visibility enhancement	13	Barreto et al. (2017), Douaioui et al. (2018), Wang (2016), Liu et al. (2018), Correa et al. (2020); Markov and Vitliemov (2020), Oleśków-Szłapka and Stachowiak (2019), Affia and Aamer (2021), Nantee and Sureeyatanapas (2021), Song et al. (2021), Winkelhaus and Grosse (2020), Woschank and Zsifkovits (2021)
	Human error reduction	9	Karunarathna et al. (2019), Lee et al. (2018) Nantee and Sureeyatanapas (2021), Oleśków-Szłapka and Stachowiak (2019), Plakas et al. (2020), Wang (2016), Winkelhaus and Grosse (2020), Zoubek et al. (2021), Zoubek and Simon (2021)
	Human resource management and safety enhancement	11	Cimini et al. (2019, 2021), Halawa et al. (2020), Nantee and Sureeyatanapas (2021), Winkelhaus and Grosse (2020)
	Sustainability improvement	4	Buntak et al. (2019), Krishnan and Wahab (2019), Nantee and Sureeyatanapas (2021), Strandhagen et al. (2017)
	Increased customer satisfaction and loyalty	9	Kekana et al. (2020), Markov and Vitliemov (2020), Nantee and Sureeyatanapas (2021)
Barriers and criticalities (RQ3)	Strategic	6	Affia and Aamer (2021), Jung and Kim (2015), Liu et al. (2018), Tran-Dang et al. (2020), Wang (2016), Wen et al. (2018)
	Economic	12	Affia and Aamer (2021), Correa et al. (2020), Cyplik et al. (2019), Feng and Ye (2021), Kawa (2015), Markov and Vitliemov (2020), Oleśków-Szłapka and Stachowiak (2019), Poenicke et al. (2019), Schmidtke et al. (2018), Tran-Dang et al. (2020), Verma et al. (2020), Zoubek and Simon (2021)
	Technological	14	Affia and Aamer (2021), Correa et al. (2020), Cyplik et al. (2019), Ding et al. (2021), Feng and Ye (2021), Kawa (2015), Liu et al. (2018), Oleśków-Szłapka and Stachowiak (2019), Schmidtke et al. (2018), Stachowiak et al. (2019), Tran-Dang et al. (2020), Verma et al. (2020), Wang (2016), Zoubek and Simon (2021)
	Cultural	6	Affia and Aamer (2021), Correa et al. (2020), Mahroof (2019), Schmidtke et al. (2018), Verma et al. (2020), Zoubek and Simon (2021)
	Safety and Security	14	Barreto et al. (2017), Cheng et al. (2019), Ding et al. (2021), Hamdy et al. (2018), Jamai et al. (2020), Liu et al. (2018), Markov and Vitliemov (2020), Schmidtke et al. (2018), Song et al. (2021), Trab et al. (2017), Tran-Dang et al. (2020), Verma et al. (2020), Wen et al. (2018), Zhu et al. (2020)

Table A1

Documents resulting from the SLR

Reference	Year	Title	First Author’s country	Methodology	RQ1	RQ2	RQ3
Woschank and Zsifkovits (2021)	2021	Smart Logistics Conceptualization and Empirical Evidence	Austria	Conceptual		X
Zoubek and Simon (2021)	2021	A framework for a Logistics 4.0 maturity model with a specification for internal logistics	Czech Republic	Conceptual	X	X	X
Zoubek et al. (2021)	2020	Methodology proposal for storage rationalization by implementing principles of Industry 4.0 in a technology-driven warehouse	Czech Republic	Conceptual	X	X
Kekana et al. (2020)	2020	The impact of smart-warehousing on a local foodservice equipment-company’s external customers	South Africa	Empirical		X
Zhu et al. (2020)	2020	A Forwarding Secrecy Based Lightweight Authentication Scheme for Intelligent Logistics	China	Analytical			X
Markov and Vitliemov (2020)	2020	Logistics 4.0 and supply chain 4.0 in the automotive industry	Bulgaria	Empirical		X	X
Jamai et al. (2020)	2020	Security issues in Industry 4.0	Tunisia	Conceptual			X
Boonsothonsatit et al. (2020)	2020	Strategic Design for Warehouse 4.0 Readiness in Thailand	Thailand	Analytical	X
Gialos and Zeimpekis (2020)	2020	Testing vision picking technology in warehouse operations: Evidence from laboratory experiments	Greece	Action research		X
Woschank and Pacher (2020a)	2020	Program planning in the context of industrial logistics engineering education	Austria	Empirical	X
Woschank and Pacher (2020b)	2020	A holistic didactical approach for industrial Logistics engineering education in the LOGILAB at the Montanuniversitaet Leoben	Austria	Empirical	X
Verma et al. (2020)	2020	Risk and resilience analysis for industry 4.0 in achieving the goals of smart logistics: An overview	India	Empirical			X
Correa et al. (2020)	2020	IoT and BDA in the Brazilian future Logistics 4.0 scenario	Brazil	Empirical		X	X
Agalianos et al. (2020)	2020	Discrete event simulation and digital twins: Review and challenges for logistics	Greece	Literature review		X
Plakas et al. (2020)	2020	A proposed technology solution for enhancing order picking in warehouses and distribution centers based on a gamified augmented reality application	Greece	Action Research		X
Krishnan and Wahab (2019)	2019	A Qualitative Case Study on the Adoption of Smart Warehouse Approaches in Malaysia	Malaysia	Empirical	X	X
Stachowiak et al. (2019)	2019	Triple Helix Model: The Role of Cooperation between Academy, Economy and Public Sector for Increasing Readiness for Logistics 4.0	Poland	Empirical	X
Karunarathna et al. (2019)	2019	A study of the implications of Logistics 4.0 in future warehousing: A Sri Lankan perspective	Sri Lanka	Literature review		X
Poenicke et al. (2019)	2019	Planning method for IoT applications in logistics	Germany	Analytical			X
Wen et al. (2018)	2018	Swarm Robotics Control and Communications: Imminent Challenges for Next Generation Smart Logistics	China	Conceptual		X	X
Liu et al. (2018)	2018	CPS-based smart warehouse for industry 4.0: A survey of the underlying technologies	China	Conceptual		X	X
Hamdy et al. (2018)	2018	Towards a smart warehouse management system	Egypt	Conceptual		X	X
Feng and Ye (2021)	2021	Operations management of smart logistics: A literature review and future research	China	Literature review	X		X
Affia and Aamer (2021)	2021	An Internet of things-based smart warehouse infrastructure: design and application	Indonesia	Empirical	X	X	X
Zhang et al. (2021)	2021	Artificial intelligence in E-commerce fulfillment: A case study of resource orchestration at Alibaba’s Smart Warehouse	China	Empirical		X
Nantee and Sureeyatanapas (2021)	2021	The impact of Logistics 4.0 on corporate sustainability: a performance assessment of automated warehouse operations	Thailand	Empirical		X
Song et al. (2021)	2020	Applications of the internet of Things (IoT) in Smart Logistics: A Comprehensive Survey	China	Literature review		X	X
Tran-Dang et al. (2020)	2020	The Internet of Things for Logistics: Perspectives, Application Review, and Challenges	South Korea	Literature review			X
Cimini et al. (2021)	2021	How human factors affect operators’ task evolution in Logistics 4.0	Italy	Empirical		X
Issaoui et al. (2021)	2020	Toward Smart Logistics: Engineering Insights and Emerging Trends	Morocco	Literature review		X
Halawa et al. (2020)	2020	Introduction of a real time location system to enhance the warehouse safety and operational efficiency	USA	Empirical		X
Granillo et al. (2020)	2020	Smart Logistics based on the Internet of things technology: an overview	China	Literature review			X
Barczak et al. (2019)	2019	Analysis of the Risk Impact of Implementing Digital Innovations for Logistics Management	Poland	Empirical	X
Buntak et al. (2019)	2019	Internet of things and smart warehouses as the future of logistics	Croatia	Conceptual		X
Winkelhaus and Grosse (2020)	2019	Logistics 4.0: a systematic review towards a new logistics system	Germany	Literature review		X
Mahroof (2019)	2019	A human-centric perspective exploring the readiness towards smart warehousing: The case of a large retail distribution warehouse	United Kingdom	Empirical	X		X
Cyplik et al. (2019)	2019	Building a model for assessing the maturity of Polish enterprises in terms of Logistics 4.0 assumptions	Poland	Empirical			X
Domański (2019)	2019	Logistics 4.0 in warehousing - current state and trends	Poland	Literature review		X
Oleśków-Szłapka and Stachowiak (2019)	2018	The Framework of Logistics 4.0 Maturity Model	Poland	Conceptual	X	X	X
Loureiro et al. (2020)	2020	Logistics 4.0: The Cooperative Strategy and Reducing Costs	Portugal	Literature review		X
Cimini et al. (2019)	2019	Exploring human factors in Logistics 4.0: empirical evidence from a case study	Italy	Empirical		X
Cheng et al. (2019)	2019	A Learnable Unmanned Smart Logistics Prototype System Design and Implementation	Taiwan	Action Research			X
Modrak et al. (2019)	2019	Mapping Requirements and Roadmap Definition for Introducing I4.0 in SME Environment	Slovakia	Empirical	X
Douaioui et al. (2018)	2018	The interaction between industry 4.0 and smart logistics: concepts and perspectives	Morocco	Literature review		X
Wrobel-Lachowska et al. (2018)	2018	ICT in Logistics as a Challenge for Mature Workers. Knowledge Management Role in Information Society	Poland	Empirical	X
Lee et al. (2018)	2018	Design and application of Internet of things-based warehouse management system for smart logistics	China	Analytical		X
Schmidtke et al. (2018)	2018	Technical Potentials and Challenges within Internal Logistics 4.0	Germany	Literature review			X
Strandhagen et al. (2017)	2017	Logistics 4.0 and emerging sustainable business models	Norway	Conceptual		X
Trab et al. (2017)	2017	A communicating object’s approach for smart logistics and safety issues in warehouses	Tunisia	Analytical			X
Barreto et al. (2017)	2017	Industry 4.0 implications in Logistics: an overview	Portugal	Literature review		X	X
Kuczyńska-Chałada et al. (2018)	2018	The challenges for logistics in the aspect of Industry 4.0	Poland	Conceptual		X
Lourenco et al. (2017)	2016	On the design of the ROBO-PARTNER Intra-factory Logistics Autonomous Robot	Portugal	Simulation		X
Wang (2016)	2016	Logistics 4.0 Solution New Challenges and Opportunities	Norway	Empirical		X	X
Jung and Kim (2015)	2015	Big Data Governance for Smart Logistics: A Value-Added Perspective	Korea	Empirical			X
Kawa (2015)	2012	SMART Logistics Chain	Poland	Conceptual		X	X
Nazir et al. (2019)	2019	Challenges for Logistics Education in Industry 4.0	Poland	Empirical	X

Note(s): * The term “empirical” refers to case studies, interviews, and surveys, while the term “action research” refers to the implementation of a Logistics 4.0 technology