How to Manage People Underutilization in an Industry 4.0 Environment?

D’Antonio, Gianluca; Chiabert, Paolo

doi:10.1007/978-3-030-01614-2_42

Cited by 6 publications

(2 citation statements)

References 19 publications

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“…However, an eighth waste, called underutilized people, was later added to Taichi Ohno's original list (Wahab et al 2013). This waste brings together the individual's intellectual property loss, as well as the inadequate arrangement of the workforce, which results from more people involved than is necessary to perform a certain task (Wahab et al 2013, D'antonio & Chiabert 2018.…”

Section: Production Wastementioning

confidence: 99%

Recognition of wastes from value co-creation in industrial services in startups

Bonamigo

Barbosa²,

Werner³

et al. 2022

Int. J. Innov.

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Objective of the study: This study aims to identify the wastes from the value co-creation in industrial services in the startups context. In addition, through the dynamic systems approach, to analyze the interaction among the wastes in the startups' value co-creation.Design/methodology/approach: First, we conducted a systematic literature review based on the Systematic Search Flow method (SSF) and the content analysis following Bardin (2011), then, through the dynamic systems approach, this step, we verify the interaction and behavior among these wastes in the value co-creation context.Findings: Based on the finds, we recognized six wastes from the value co-creation in startups. We evidenced that waste "Personal Characteristics" was pointed was the greatest impact on co-creation concerning other wastes.Originality: This is the first paper that recognizes and behavior evaluates the wastes from value cocreation in industrial service based on the dynamic of systems approach for the startups.Research limitations/implications: The wastes recognized were based on current literature. An empirical test can be a way to identify other wastes and evaluation these finds in the practice.Practical implications: The listed wastes can serve as a basis to guide strategies for mitigating or eliminating these losses in the value co-creation process in startups. In addition, directing players in decision-making anticipated way from different perspectives to improve collaboration among multiple companies without wastes.Social implications: Once the value cocreation process is more efficient, the societal can receive more benefits and enhance well-being, through services new or services improved offerings for society via startups.

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Section: Production Wastementioning

confidence: 99%

Recognition of wastes from value co-creation in industrial services in startups

Bonamigo

Barbosa²,

Werner³

et al. 2022

Int. J. Innov.

View full text Add to dashboard Cite

show abstract

“…The organizations also face difficulty in identifying and selecting the appropriate technologies for their processes. Another important challenge is to remove the fear of losing the jobs among the workforce and to upgrade their skills and knowledge to deal with automated systems (D'antonio and Chiabert, 2018; Bag and Wood, 2020; Raj et al , 2020). The organizations are also struggling for developing concrete policies for future workforce.…”

Section: Introductionmentioning

confidence: 99%

Developing human resource for the digitization of logistics operations: readiness index framework

Gupta

Singh

Gupta

2021

IJM

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PurposeThe purpose of this study is to identify factors that are important for logistics organizations from the perspective of manpower readiness for digitization of logistics operations. The study also prioritizes the identified factors and also evaluates the readiness index of manpower for the digitalization of logistics processes.Design/methodology/approachThe factors for manpower readiness are identified through literature review and analysis of a case study. Three major categories of factors are identified. These are organizational, behavioural and technological factors. Under these three major categories of factors, 18 sub-factors are identified. Thereafter, with experts' inputs, the factors are prioritized using Fuzzy analytic hierarchy process (AHP). Further, a case illustration of an Indian logistics company has been taken to understand the current processes, technical capabilities, manpower skills and organization culture. After the case analysis and expert inputs, the manpower readiness index has been evaluated by using graph theory matrix approach (GTMA).FindingsThe prioritization of manpower readiness factors has been done using Fuzzy AHP. Organizational factors are found to be the most important factors which require quick attention. Sub-factors that are most important for building competencies in the logistics sector are providing the right training on functional skill development (0.129), top management support and commitment for digitalization (0.117), and organizational culture for process digitalization (0.114), etc. Finally, framework for evaluation of manpower readiness index for logistics operations in the digital age has been illustrated for a case company.Practical implicationsIndian logistics companies can benchmark their readiness index with respect to the best in the industry. Based on the readiness index, logistics companies can analyse their position, gaps from best and worst and can also identify potential areas for improvement.Originality/valueThe novelty of the study lies in the development of a framework for manpower readiness for digitalization in the logistics sector. In literature, this field is very less researched and provides the scope for developing strategies for improving manpower competencies for Industry 4.0. Logistics companies can improve their performance by making their manpower ready based on results obtained for readiness index.

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