Industrial sustainability: Modelling drivers and mechanisms with barriers

Neri, Alessandra; Cagno, Enrico; Sebastiano, Giulio Di; Trianni, Andrea

doi:10.1016/j.jclepro.2018.05.140

Cited by 81 publications

(56 citation statements)

References 145 publications

(474 reference statements)

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“…In general, in the context of industry, there are three issues of sustainability that have been extensively discussed: Corporate sustainability, manufacturing sustainability, and industrial sustainability [26]. Corporate sustainability represents the actions of strategies; manufacturing sustainability is associated with the production system; and industrial sustainability refers to the plant level in manufacturing industries that involves various actions comprised of materials, products, process, plants, and production systems [27].…”

Section: Industrial Sustainabilitymentioning

confidence: 99%

“…After the calculation of the total influence matrix, the next step is to convert these matrices into the posterior matrix utilizing Equations (24) to (26). The posterior matrix is derived as shown below:…”

Section: Br-dematelmentioning

confidence: 99%

“…In this step, Bayesian theory is also taken into consideration. The posterior rough total influence matrix, T, can then be derived based on Equations (24) to (26). Based on Equation (28), the reliability of the collected data can be derived.…”

Section: The Derivation Of the Causal Network Via The Bayesian Rough mentioning

confidence: 99%

See 2 more Smart Citations

Systemic Functions Evaluation based Technological Innovation System for the Sustainability of IoT in the Manufacturing Industry

2019

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Technological innovations are regarded as the tools that can stimulate economic growth and the sustainable development of technology. In recent years, as technologies based on the internet of things (IoT) have rapidly developed, a number of applications based on IoT innovations have emerged and have been widely adopted by various public and private sectors. Applications of IoT in the manufacturing industry, such as manufacturing intelligence, not only play a significant role in the enhancement of industrial competitiveness and sustainability, but also influence the diffusion of innovative applications that are based on IoT innovations. It is crucial for policy makers to understand these potential reasons for stimulating IoT industrial sustainability, as they can facilitate industrial competitiveness and technological innovations using supportive means, such as government procurement and financial incentives. Therefore, there is a need to ascertain different factors that may affect IoT industrial sustainability and further explore the relationship between these factors. However, finding a set of factors that affects IoT industrial sustainability is not easy. Recently, the robustness of a theoretical framework, termed the technological innovation system (TIS), has been verified and has been used to explore and analyze technological and industrial development. Thus, it is suitable for this research to use this theoretical model. In order to find out appropriate factors and accurately analyze the causality among factors that influence IoT industrial sustainability, this research presents a Bayesian rough Multiple Criteria Decision Making (MCDM) model based on TIS functions by integrating random forest (RF), decision making trial and evaluation (DEMATEL), Bayesian theory, and rough interval numbers. The proposed analytical framework is validated by an empirical case of defining the causality between TIS functions to enable the industrial sustainability of IoT in the Taiwanese smart manufacturing industry. Based on the empirical study results, the cause group consists of entrepreneurial activities, knowledge development, market formation, and resource mobilization. The effect group is composed of knowledge diffusion through networks’ guidance of the search, and creation of legitimacy. Moreover, the analytical results also provide several policy suggestions promoting IoT industrial sustainability that can serve as the basis for defining innovation policy tools for Taiwan and late coming economies.

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Section: Industrial Sustainabilitymentioning

confidence: 99%

Section: Br-dematelmentioning

confidence: 99%

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Systemic Functions Evaluation based Technological Innovation System for the Sustainability of IoT in the Manufacturing Industry

2019

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“…An unbalanced approach to sustainability was observed, economic sustainability being relatively more mature (15%) than ecologic (9%) and social (7%), which is a highly common industrial case (Neri et al, 2018).…”

Section: Step 0 -Identification Of Key Stakeholders and Sustainabilitmentioning

confidence: 99%

Setting a framework for organisational sustainable development

Bastas

Liyanage

2019

Sustainable Production and Consumption

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Increasing worldwide demand for products and services is applying a significant pressure on firms and supply chains operationally and financially, along with negative implications on our planet and the public. New perspectives and approaches are required to be adopted by all members of the society, including the businesses for sustainable development. However, enabling such integration from an organisational management perspective is not straightforward, due to complexities and conflicts associated with balanced integration of economic, environmental and social agendas. Aimed towards addressing this important industrial and societal research requirement, a tailored framework is presented, constructed upon the deeply rooted management principles of quality management (QM) and supply chain management (SCM) to facilitate integration of triple bottom line sustainability into business management. The framework outlines the practical steps for implementation of such an approach, including the quantitative, current state maturity assessment as one of the key application steps. This approach is taken forward to an application step, at an organisation in Cyprus, undertaken through the action research study method that enabled demonstrating both its application, and its positive effects on the sustainable development of the participating organisation. Several contributions are made, including the formulation of a practical approach to organisational integration of triple bottom line sustainability through QM and SCM. Particularly, a new management perspective was introduced with implications to many organisational managers that adopt ISO 9001 and supply chain integration principles, setting a framework for extending these principles beyond their original QM and SCM agendas towards organisational sustainable development.

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“…Specifically, there have been some past studies on organizational change for sustainability performance in the manufacturing sector with focus on examining the barriers to change (Neri, Cagno, Di Sebastiano, & Trianni, 2018;Thomas-Seale, Kirkman-Brown, Attallah, Espino, & Shepherd, 2018;Trianni, Cagno, & Neri, 2017). However, organizational change becomes a driver of sustainable performance in the metal manufacturing industry (Feng, Huang, & Wang, 2018;Orji, 2019).…”

Section: Organizational Changementioning

confidence: 99%

Investigating the Relationships Between Organizational Change, Organizational Climate, and Organizational Performance

Supriyati¹,

Udin²,

Wahyudi³

et al. 2019

IJFR

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This study aims to analyze the effect of organizational change (i.e., technostructure change, work procedure, and individual) on organizational climate and organizational performance. By using the census technique, the respondents are all employees of regional drinking water company (PDAM) in Kendal regency of Indonesia. Data are analyzed using simple and multiple regression analysis. The results show that technostructure change partially has a significant negative effect on organizational climate, while work procedure and individual change have a significant positive effect on organizational climate. Furthermore, organizational change simultaneously has a significant positive effect on organizational climate and organizational performance.

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Industrial sustainability: Modelling drivers and mechanisms with barriers

Cited by 81 publications

References 145 publications

Systemic Functions Evaluation based Technological Innovation System for the Sustainability of IoT in the Manufacturing Industry

Systemic Functions Evaluation based Technological Innovation System for the Sustainability of IoT in the Manufacturing Industry

Setting a framework for organisational sustainable development

Investigating the Relationships Between Organizational Change, Organizational Climate, and Organizational Performance

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