Value creation during fourth industrial revolution: Use of intellectual capital by most innovative companies of the world

Xin, Li; Nosheen, Safia; Haq, Naveed Ul; Gao, Xue

doi:10.1016/j.techfore.2020.120479

Cited by 54 publications

(66 citation statements)

References 62 publications

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“…Organisations will require a leader who is competent in developing, managing, and or deploying sensors, actuators and the Internet of Things (IoT) (smart technology) to fully support technical processes supporting green initiatives (Haenlein and Kaplan, 2021;Li et al, 2020). Additionally, the use of robotics, bots and or chatbots is also relevant for boosting digital operations, and a leader with the technical knowhow could prove essential for managing operations not limited to robotic process automation (Haenlein and Kaplan, 2021;Li et al, 2020). Likewise, studies advocate that possessing knowledge of artificial intelligence and algorithms, and the ability to implement them is fundamental to organisational growth in today's rapidly transforming digitalised world (Sarc et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Challenged by the pressures of government programmes to address global warming concerns amid the rising volatility of the fourth industrial revolution's (4IR) advances in smart technology, artificial intelligence, robotics, algorithms (STARA), and digitalisation, organisational leaders face an imperative to develop and retain staff talent to address global climate change and organisational sustainability (Brougham and Haar, 2018;Li et al, 2020;Nirino et al, 2020;Pinto, 2017). The global war for talent and how to manage talent remain major challenges for organisations, especially given that talent familiar with 4IR technologies is needed to help organisations respond to the United Nations Global Compact (UNGC) to foster environmental sustainability (Ariss et al, 2014;Bamel et al, 2020;Farndale et al, 2020;Gardas et al, 2019;John et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…By demonstrating STARA-related competencies via an application of one or more of the STARA components, leaders can effectively catalyse initiatives relevant for achieving organisational green objectives (Oosthuizen, 2019). Given technological change, it is important for leaders to go beyond just possessing basic skills and competencies as they may not be sufficient to combat future challenges provoked by the 4IR (Li et al, 2020). For organisations to win in the short run, bolster competitive edge and survive in the long run, leaders must cultivate JIC 23,1 competencies fundamental to STARA (Masood and Egger, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Green talent management and turnover intention: the roles of leader STARA competence and digital task interdependence

Ogbeibu

Jabbour

Burgess

et al. 2021

JIC

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PurposeCongruent with the world-wide call to combat global warming concerns within the context of advancements in smart technology, artificial intelligence, robotics, algorithms (STARA), and digitalisation, organisational leaders are being pressured to ensure that talented employees are effectively managed (nurtured and retained) to curb the potential risk of staff turnover. By managing such talent(s), organisations may be able to not only retain them, but consequently foster environmental sustainability too. Equally, recent debates encourage the need for teams to work digitally and interdependently on set tasks, and for leaders to cultivate competencies fundamental to STARA, as this may further help reduce staff turnover intention and catalyse green initiatives. However, it is unclear how such turnover intention may be impacted by these actions. This paper therefore, seeks to investigate the predictive roles of green hard and soft talent management (TM), leader STARA competence (LSC) and digital task interdependence (DTI) on turnover intention.Design/methodology/approachThe authors used a cross-sectional data collection technique to obtain 372 useable samples from 49 manufacturing organisations in Nigeria.FindingsFindings indicate that green hard and soft TM and LSC positively predict turnover intention. While LSC amplifies the negative influence of green soft TM on turnover intention, LSC and DTI dampen the positive influence of green hard TM on turnover intention.Originality/valueOur study offers novel insights into how emerging concepts like LSC, DTI, and green hard and soft TM simultaneously act to predict turnover intention.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Green talent management and turnover intention: the roles of leader STARA competence and digital task interdependence

Ogbeibu

Jabbour

Burgess

et al. 2021

JIC

View full text Add to dashboard Cite

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“…IC and FP. Industry 4.0 is reshaping policies that pertain to innovation, and the importance of IC has emerged as a critical determinant for businesses sustainability [36,37].…”

Section: Ic Definition and Measurement Many Researchers Havementioning

confidence: 99%

Exploring the Nonlinear Effect of Intellectual Capital on Financial Performance: Evidence from Listed Shipping Companies in China

Zhang

2021

Complexity

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Intellectual capital (IC) is reckoned as a significant driving force of competitive advantage and financial sustainability of any organization. The study’s objective is to explore the nonlinear effect of IC and its components on financial performance (FP) of China’s listed shipping companies over a six-year period (2014–2019). The modified Value Added Intellectual Coefficient (MVAIC) model is used to systematically assess IC. The empirical results show an inverted U-shaped relationship between the aggregate IC and FP (measured through return on assets). Regarding IC components, human, relational, and innovation capitals have an inverted U-shaped relationship with FP, while the quadratic relationship between structural capital and FP is not significant. In addition, physical capital has a U-shaped relationship with FP. This study will offer some new insights for corporate managers to improve firms’ FP by effectively utilizing their IC resources.

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“…The importance of developing digital skills of the workforce for ensuring the sustainability of economic development in the context of Industry 4.0, based on the digitalization of production processes, is highlighted in an article by European scientists (Habanik et al, 2019). Researchers from China and Pakistan state the crucial importance of intellectual capital and innovation policy for manufacturing companies in the context of the fourth industrial revolution (Li et al, 2021). Improving human capital contributes to the growth of the effectiveness of technological innovation, strengthening the link between technological innovation and spillovers (Hu, 2021).…”

Section: Theoretical Foundations Of the Relationship Between Industrial Growth And Innovative Developmentmentioning

confidence: 99%

Models of Regional Development in Russia: Level of Industrialisation and Innovative Performance

Doroshenko

Starikova

Ряпухина

2021

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The growth in the share of industry in the structure of Gross Domestic Product due to an increase in its competitiveness, causes a multiplier effect of accelerating economic growth, reducing unemployment and developing social and transport infrastructure. All these imperatives actualise the task of deepening the analysis of the level of industrialisation and innovative performance of the national economy and its regions. To achieve this goal, a theoretical analysis of the relationship between industrial growth and innovation activity was carried out, and the problems of industrial growth of the Russian economy were identified. The proposed toolkit is based on assessing the level of industrialization and innovative performance of the region. Based on their comparison, four models of industrial and innovative development are distinguished: model of non-industrial development, model of post-industrial development, model of neo-industrial development, and model of industrial development. According to the results of the study, the structure of Russian regions by the type of industrial-innovative development model is relatively stable and insufficiently progressive. Only a third of the regions have high innovative performance. The lack of the required balance between the development of industrial potential and the innovative productivity of Russian regions is associated with the low efficiency of the applied industrial policy measures. The research results can be useful for assessing the quality of industrial growth of regions in countries with transitional economies.

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Value creation during fourth industrial revolution: Use of intellectual capital by most innovative companies of the world

Cited by 54 publications

References 62 publications

Green talent management and turnover intention: the roles of leader STARA competence and digital task interdependence

Green talent management and turnover intention: the roles of leader STARA competence and digital task interdependence

Exploring the Nonlinear Effect of Intellectual Capital on Financial Performance: Evidence from Listed Shipping Companies in China

Models of Regional Development in Russia: Level of Industrialisation and Innovative Performance

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