A human-centric perspective exploring the readiness towards smart warehousing: The case of a large retail distribution warehouse

Can artificial intelligence’s limitations drive innovative work behaviour?

Artificial intelligence (AI) is deemed to increase workers’ productivity by enhancing their creative abilities and acting as a general-purpose tool for innovation. While much is known about AI’s ability to create value through innovation, less is known about how AI’s limitations drive innovative work behaviour (IWB). With AI’s limits in perspective, innovative work behaviour might serve as workarounds to compensate for AI limitations. Therefore, the guiding research question is: How will AI limitations, rather than its apparent transformational strengths, drive workers’ innovative work behaviour in a workplace? A search protocol was employed to identify 65 articles based on relevant keywords and article selection criteria using the Scopus database. The thematic analysis suggests several themes: (i) Robots make mistakes, and such mistakes stimulate workers’ IWB, (ii) AI triggers ‘fear’ in workers, and this ‘fear’ stimulates workers’ IWB, (iii) Workers are reskilled and upskilled to compensate for AI limitations, (iv) AI interface stimulates worker engagement, (v) Algorithmic bias requires IWB, and (vi) AI works as a general-purpose tool for IWB. In contrast to prior reviews, which generally focus on the apparent transformational strengths of AI in the workplace, this review primarily identifies AI limitations before suggesting that the limitations could also drive innovative work behaviour. Propositions are included after each theme to encourage future research.

Can artificial intelligence’s limitations drive innovative work behaviour?

Artificial intelligence (AI) is deemed to increase workers’ productivity by enhancing their creative abilities and acting as a general-purpose tool for innovation. While much is known about AI’s ability to create value through innovation, less is known about how AI’s limitations drive innovative work behaviour (IWB). With AI’s limits in perspective, innovative work behaviour might serve as workarounds to compensate for AI limitations. Therefore, the guiding research question is: How will AI limitations, rather than its apparent transformational strengths, drive workers’ innovative work behaviour in a workplace? A search protocol was employed to identify 65 articles based on relevant keywords and article selection criteria using the Scopus database. The thematic analysis suggests several themes: (i) Robots make mistakes, and such mistakes stimulate workers’ IWB, (ii) AI triggers ‘fear’ in workers, and this ‘fear’ stimulates workers’ IWB, (iii) Workers are reskilled and upskilled to compensate for AI limitations, (iv) AI interface stimulates worker engagement, (v) Algorithmic bias requires IWB, and (vi) AI works as a general-purpose tool for IWB. In contrast to prior reviews, which generally focus on the apparent transformational strengths of AI in the workplace, this review primarily identifies AI limitations before suggesting that the limitations could also drive innovative work behaviour. Propositions are included after each theme to encourage future research.

Harmony in intelligent hybrid teams: the influence of the intellectual ability of artificial intelligence on human members’ reactions

Purpose

The purpose of this paper was to investigate the relationships among the intellectual ability of artificial intelligence (AI), cognitive emotional processes and the positive and negative reactions of human members. The authors also examined the moderating role of AI status in teams.

Design/methodology/approach

The authors designed an experiment and recruited 120 subjects who were randomly distributed into one of three groups classified by the upper, middle and lower organization levels of AI in the team. The findings in this study were derived from subjects’ self-reports and their performance in the experiment.

Findings

Regardless of the position held by AI, human members believed that its intelligence level is positively correlated with dependence behavior. However, when the AI and human members are at the same level, the higher the intelligence of AI, the more likely it is that its direct interaction with team members will lead to conflicts.

Research limitations/implications

This paper only focuses on human–AI harmony in transactional work in hybrid teams in enterprises. As AI applications permeate, it should be considered whether the findings can be extended to a broader range of AI usage scenarios.

Practical implications

These results are helpful for understanding how to improve team performance in light of the fact that team members have introduced AI into their enterprises in large quantities.

Originality/value

This study contributes to the literature on how the intelligence level of AI affects the positive and negative behaviors of human members in hybrid teams. The study also innovatively introduces “status” into hybrid organizations.

The transformation from manual to smart warehousing: an exploratory study with Swedish retailers

Purpose

To meet customers' expectations on shorter lead times, high product availability, flexibility, and variation in delivery and return options, retailers have turned their attention to warehousing and are making big investments in technology. Currently, technology providers are pushing for smart warehousing, a new and under-researched phenomenon. This study aims to conceptualize the term and examine pathways toward implementing smart warehousing.

Design/methodology/approach

An exploratory survey was administered to 50 leading Swedish retailers in varying segments. A two-tailed t-test for equality of means was used to detect significant differences between current and future states.

Findings

The study found that future smart warehouses will be automated, autonomous, digital, and connected, but that retailers will follow different paths along this journey, driven by contextual trends, e.g. sales growth, wider product assortment, shorter lead-time offerings, and integration of brick-and-mortar and online stores. Interestingly, the study revealed that many of the retailers that aim to create smart warehouses in five years are not the retailers with the most developed technology today.

Research limitations/implications

The paper operationalizes smart warehousing in two dimensions: degree of automation and degree of digitalization and connectivity of information platforms. Based on the findings, 16 theoretical propositions are put forth that, based on contextual factors, explain different pathways for retailers to implement smart warehousing.

Practical implications

The empirical insights and theoretical discussions provide practically useful guidance, including outlined trends, for selecting and benchmarking automation and complementary technologies in warehouse operations.

Originality/value

This paper conceptualizes and operationalizes smart warehousing – an original approach. It is also one of the first to investigate the technological transformation in retail warehousing empirically, explaining how and why retailers choose different pathways toward smart warehousing.

Exploring the Impact of Technology 4.0 Driven Practice on Warehousing Performance: A Hybrid Approach

Developing a promising technology that copes with the industrial warehousing environment requires special preparation. It includes infrastructure, equipment, resources, knowledge, efficiencies, and strategies for dealing with failures. This study examines Technology 4.0 driven warehouse practices and performance based on a thorough literature review. The study presents a unique proposition as it considers a two-fold fuzzy Delphi analysis to rank the Technology 4.0 driven practices using best-worst method (BWM) based on experts’ responses. Warehouse performance measures are evaluated by the Combined Compromise Solution (CoCoSo) method. The results indicate the contributions of a ‘Man-machines or robots for facilitating human’; ‘Planning system for management’; ‘Storage systems’ as as leading practices contributing to ‘improved inventory management’, ‘effective storage and distribution’, and ‘improved distribution and shipping or delivery process’. Using this study, researchers and managers will better understand how to adopt technology in warehouse management system.

Research themes in machine learning applications in supply chain management using bibliometric analysis tools

Purpose

This paper conducts a Systematic Literature Review (SLR) of Machine Learning (ML) in Supply Chain Management through bibliometric and network analysis, the authors are able to grasp key features of the contemporary literature. The study makes use of state-of-the-art analytical framework based on a unified approach to reveal insights from the present body of knowledge and the potentials for future research developments.

Design/methodology/approach

Unlike standard literature reviews, in SLR, a structured approach is followed. The approach enables utilizing contemporary tools and software packages such as R-package “bibliometrix” and Gephi for exploratory and visual analytics. A number of clustering methods are employed to form clusters. Later, multivariate analysis methodologies are adopted to determine the dominant clusters for the influential co-cited references.

Findings

Using contemporary tools from Bibliometric Analysis (BA), the authors identify in an exploratory analysis, the influential authors, sources, regions, affiliations and papers. In addition, the use of network analysis tools reveals research clusters, topological analysis, key research topics, interrelation and authors’ collaboration along with their patterns. Finally, the optimum number of clusters computed for cluster analysis is decided using a systematic procedure based on multivariate analysis such as k-means and factor analysis.

Originality/value

Modern-day supply chains increasingly depend on developing superior insights from large amounts of data available from diverse sources in unstructured and semi-structured formats. In order to maintain a competitive edge, the supply chains need to perform speedy analysis of big data using efficient tools that provide real-time decision-making insights. Such an analysis necessitates automated processing using intelligent ML algorithms. Through a BA followed by a detailed data visualization in a network analysis enabled grasping key features of the contemporary literature. The analysis is based on 155 documents from the period 2008 to 2018 selected using a systematic selection procedure.

Technology-Driven Responsiveness in Times of COVID-19: A Fuzzy Delphi and Fuzzy AHP-Based Approach

Supply chain responsiveness creates value for firms and their stakeholders and is a key towards generating above-normal profits for firms. Consequently, there has been a surge of research on it, which has expanded due to the pressures to be responsive during the pandemic of COVID19. Responsiveness is an attribute wherein the supply chains are equipped to respond resolutely and within a suitable timeframe to consumer requirements. The trouble to businesses posed by COVID-19 caught several firms off-guard. Further, there is limited research on the augmentation of supply chain responsiveness through new technologies. The present research, therefore, applies a hybrid approach by combining fuzzy Delphi and fuzzy AHP to understand the technology-driven enablers of supply chain responsiveness by employing a case company in food retail. The investigation reveals that supply chain integration technologies, sustainable manufacturing technologies, and smart warehousing are the most important enablers of supply chain responsiveness in the context of food supply chains. The results aid the key enablers that need attention and resources to be directed towards these enablers to eliminate a chance of missing on a successful transition into a more responsive supply chain.

Sustainable food supply chains: overcoming key challenges through digital technologies

Purpose

The purpose of this paper is to offer a consolidative approach in exploring the potential contribution of digital technologies in sustainable supply chain management (SSCM) for the sustainable performance of food supply chain business, through the circular economy concepts.

Design/methodology/approach

As a single case study, this qualitative, interpretivist research was based on one of the largest food producers in the United Kingdom. The research utilises semi-structured interviews and applies thematic analysis to offer rich insights into SSCM challenges and their relationship with the business performance, through ten in-depth interviews.

Findings

Findings derived from thematic analysis of the interview transcripts suggest four main critical success factors underpinning SSCM practices and businesses performance – i.e. business continuity, waste reduction, performance measurement approach, and organisational learning, which could use the help of digital technologies to improve. This led to seven propositions to be addressed in the future research.

Originality/value

This research offers real, practical insights into SSCM challenges, within the context of food supply chain and explores the potential of digital technologies in overcoming them. Accordingly, the primary contribution of this work is grounded in the identification of critical success factors in SSCM for food supply chains (FSC). Hence, this work contributes further to the literature on SSCM, as well as circular economy, by providing a study of a business in the context of the highly pertinent and valuable food industry.

Safety of Food and Food Warehouse Using VIBHISHAN

Food is one of the integral parts of human life making the quality of food one of the prime factors in its selection for consumption. In order to maintain the food quality, it must be taken care of from the very first step where its quality may be affected, that is, warehouses. Food safety and safety of its warehouses is one of the major concerns, because many people lose their lives due to poor food quality. A robot that can ensure the safety of both food and warehouse can be one of the possible solutions, because taking care of huge warehouses is a tedious task and sometimes food present inside the warehouse gets unnoticed and thus get contaminated. Also safety of warehouses from intruders can be done by a robot, in any condition where it is difficult for human beings. This robot would be cheap and efficient and also make sure of safety, keeping the food intact and ensuring its fine quality.

Real-time data integration of an internet-of-things-based smart warehouse: a case study

Purpose

Creating a real-time data integration when developing an internet-of-things (IoT)-based warehouse is still faced with challenges. It involves a diverse knowledge of novel technology and skills. This study aims to identify the critical components of the real-time data integration processes in IoT-based warehousing. Then, design and apply a data integration framework, adopting the IoT concept to enable real-time data transfer and sharing.

Design/methodology/approach

The study used a pilot experiment to verify the data integration system configuration. Radio-frequency identification (RFID) technology was selected to support the integration process in this study, as it is one of the most recognized products of IoT.

Findings

The experimentations’ results proved that data integration plays a significant role in structuring a combination of assorted data on the IoT-based warehouse from various locations in a real-time manner. This study concluded that real-time data integration processes in IoT-based warehousing could be generated into three significant components: configuration, databasing and transmission.

Research limitations/implications

While the framework in this research was carried out in one of the developing counties, this study’s findings could be used as a foundation for future research in a smart warehouse, IoT and related topics. The study provides guidelines for practitioners to design a low-cost IoT-based smart warehouse system to obtain more accurate and timely data to support the quick decision-making process.

Originality/value

The research at hand provides the groundwork for researchers to explore the proposed theoretical framework and develop it further to increase inventory management efficiency of warehouse operations. Besides, this study offers an economical alternate for an organization to implement the integration software reasonably.

Implementation barriers of smart technology in Indian sustainable warehouse by using a Delphi-ISM-ANP approach

Purpose

In the digitalization era, supply chain processes and activities have changed entirely, and smart technology impacts each sustainable supply chain movement. The warehouse and distribution of various organizations have started adopting smart technologies globally. However, the adoption of smart technologies in the Indian warehousing industry is minimal. The study aims to identify the implementation barriers of smart technology in the Indian warehouse to achieve sustainability.

Design/methodology/approach

This study employs an integrated Delphi-ISM-ANP research approach. The study uses the Delphi approach to finalize the barriers identified from the detailed literature review and expert opinion. The finalized 17 barriers are modeled using interpretive structural modeling (ISM) to get the contextual relationship. The ISM method's output and analysis using the analytical network process (ANP) illustrate priorities.

Findings

The study's findings showed that the lack of government support, lack of vision and mission and the lack of skilled manpower are the most significant barriers restricting the organization from implementing smart and sustainable supply chain practices in the warehouse.

Practical implications

This study would help the practitioners enable the sustainable warehousing system or convert the existing warehouse into a smart and sustainable warehouse by developing an appropriate strategy. This study would also help reduce the impact of different barriers that would strengthen the chance of technology adoption in the warehouses.

Originality/value

The literature related to adopting smart and sustainable practices in the warehouse is scarce. Modeling of adoption barrier for smart and sustainable warehouse using an integrated research approach is the uniqueness of this study that have added value in the existing scientific knowledge.