Quality management vision of future early career operations managers

Shokri, Alireza; Nabhani, Farhad

doi:10.1108/ijqrm-06-2017-0114

Cited by 5 publications

(8 citation statements)

References 57 publications

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“…This definition is consistent with the one that Shokri and Nabhani (2019) used for early-career operation managers. Since there are still weaknesses and strengths in the different sampling techniques (Sharma, 2017), this present study's purposive sampling restricts it to context-specific generalizability.…”

Section: Methodssupporting

confidence: 78%

“…The O*NET competencies are within the premise of the STS theory and, to an appreciable extent, accord well with the TQM indicators used for early-career operation managers (Shokri and Nabhani, 2019). Also, the competencies support combining quality management expertise with data science (Park et al , 2017), embracing statistical thinking and analytical thinking for new quality thinking (Coleman, 2013) and future quality managers' adopting alternative paradigms that fit the current business era (Antony, 2013).…”

Section: Literature Reviewsupporting

confidence: 63%

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Mapping the implications and competencies for Industry 4.0 to hard and soft total quality management

Babatunde

2020

TQM

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PurposeThe purpose of this study is to map the implications and competencies for Industry 4.0 to the hard and soft aspects of total quality management (TQM).Design/methodology/approachThe author/s collected data from purposively drawn samples of early-career engineering professionals (ECEPs) using a cross-sectional survey. A total of 20 ECEPs from three small-class cohorts (2014, 2016 and 2018) participated in the survey. The author/s analyzed data using the Kruskal–Wallis test and Wilcoxon–Mann–Whitney test to establish the effect of cohort and gender on the implications and competencies for Industry 4.0. The author/s then mapped the top- and bottom-ranked implications and competencies onto the hard and soft aspects of TQM using a matrix.FindingsBased on the cohort, significant differences p < 0.05 existed in the interests and competencies for Industry 4.0. In congruence, the 2014 cohort had the highest number of “unique” top- and bottom-ranked competencies and implications spanning the hard and soft TQM. Based on gender, nonsignificant differences p < 0.05 existed in the interests and competencies for Industry 4.0. The male and female ECEPs' “common” top-ranked implications appeared under the hard and soft TQM. All their “common” top-ranked competencies appeared under the hard TQM, while all their “common” bottom-ranked competencies appeared under the soft TQM.Research limitations/implicationsThe sample size, context/discipline and perceptual data are limitations.Practical implicationsOptimizing an existing TQM framework/matrix to design Industry 4.0 TQM, advanced as TQM 4.0.Originality/valuePerspectives of early-career professionals for TQM 4.0 implementation.

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Section: Methodssupporting

confidence: 78%

Section: Literature Reviewsupporting

confidence: 63%

Mapping the implications and competencies for Industry 4.0 to hard and soft total quality management

Babatunde

2020

TQM

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“…Quality practices have been presented throughout the literature as a multifaceted concept, that focuses on quality wide improvement principles within the organisation (Asif, 2019;Basu et al, 2020). There is a plethora of studies that explored their impact on operational performance (Asif, 2019;Kaur et al, 2019;Khan et al, 2019;Shokri and Nabhani, 2019). However, some studies (Flynn et al, 1995;Kaynak, 2003) argue that quality practices are not a source of competitive advantage and might not impact the operational performance.…”

Section: Quality Practices Impact On Production Swiftness and Evennessmentioning

confidence: 99%

Quality and lean practices synergies

Onofrei¹,

Fynes²,

Nguyen³

et al. 2020

IJQRM

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PurposeThe purpose of this study is to investigate the relationship between investments in quality and lean practices, and their impact on factory fitness. Using concepts originating in the theory of swift even flow, this study asserts that manufacturers, in order to improve their production swiftness and evenness, must leverage the potential synergetic effects between quality and lean practices.Design/methodology/approachThis research uses data from the Global Manufacturing Research Group (GMRG) survey project (with data collected from 922 manufacturing plants, across 18 countries). The constructs and measurement model were assessed using confirmatory factor analysis (CFA) and the hypotheses were tested using ordinary least square (OLS) models.FindingsThis study highlights that both investments in quality and lean practices have direct impact factory fitness. The results provide insights into the efficacy of the investments in manufacturing practices and their role in augmenting the operational performance. The investments in quality practices were found to enhance the efficacy of investments in lean practices, which in turn impact the factory fitness.Practical implicationsFrom a practical perspective, the study informs managers on how to leverage investment in quality practices to enhance the impact of lean practice on performance. The results provide empirical evidence to support management decision-making concerning the development of competences in quality and lean practices, which may create competitive advantage.Originality/valueThis study contributes to the quality and lean literature and provides empirical evidence of the synergetic effects between investments in quality and lean practices. The analysis offers a greater understanding of the mechanisms that can be used to maximise the impact of investments in lean practices, from a global perspective. The findings are important to the advancement of theory in operations management, as it integrates three research streams: quality practices, lean practices and swift even flow research.

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“…The context paradigm is also called "Theory C" (Van Kemenade, 2014). Environmentally sustainable development, in the wake of climate change concerns, is an emergent change and appears in the context paradigm, i.e., in Theory C (Garza-Reyes et al, 2018;Shokri and Nabhani, 2018;Wright and Nyberg, 2017). However, there is limited emphasis on quality management models for environmental sustainability in Theory C (Shokri and Nabhani, 2018).…”

Section: Green Qualitymentioning

confidence: 99%

What does “green quality” really mean?

Gouda

Awasthy

Krishnan³

et al. 2019

TQM

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Purpose The purpose of this paper is to identify various dimensions of green quality. It integrates the existing carbon footprinting technique with the eight dimensions of quality proposed by Garvin (1984, 1987). Apart from extending these concepts, it also proposes two new dimensions – traceability and standardization which are not explicitly considered by the above two. Design/methodology/approach Conceptual theory building is used to develop a framework consisting of three interrelated propositions which explain the underlying dimensions of green quality and provide a better understanding of the same. Findings Similar to the eight dimensions of quality proposed by Garvin, the authors propose various dimensions of green quality and develop three propositions around these dimensions. This conceptual framework is developed by integrating the works of traditional quality (specifically Garvin’s eight dimensions), emergent literature on green products and their attributes, carbon footprinting from environmental economics discipline by summarizing their common elements and contrasting their differences. Originality/value This research is one of the first studies that explore the dimensions of green quality of a product. Apart from discovering and exploring inherent greenness in Garvin’s eight dimensions of quality, the authors also discuss about two new dimensions – traceability and standardization.

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Quality management vision of future early career operations managers

Cited by 5 publications

References 57 publications

Mapping the implications and competencies for Industry 4.0 to hard and soft total quality management

Mapping the implications and competencies for Industry 4.0 to hard and soft total quality management

Quality and lean practices synergies

What does “green quality” really mean?

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