Tahmineh Raoofi and Sahin Yasar
This study aims to elaborate on the existing link between maintenance practices and the digital world while also highlighting any unaddressed potential for digital transformation…
Abstract
Purpose
This study aims to elaborate on the existing link between maintenance practices and the digital world while also highlighting any unaddressed potential for digital transformation in aircraft maintenance. Additionally, explore how digital technologies contribute to optimizing efficiency within the continuing airworthiness management (CAM) processes.
Design/methodology/approach
A literature review was performed to provide a precise review of the authority regulations on CAM processes and existing literature on digital transformation, including artificial intelligence, machine learning, neural network and big data in civil aircraft maintenance and continuing airworthiness processes. This method is used to organize, analyze and structure the body of literature to identify research gaps in the selected scope of the study.
Findings
The high position of digital technologies in preventive and predictive maintenance and the need for legislative development for using them in CAM are emphasized. Moreover, it is shown in which area of CAM scientific research has been performed regarding the application of frontier digital technologies. In addition, the gaps between maintenance practices and the digital world, along with the potential scopes of digital transformation which has not been well addressed, are identified. And finally, how digital technologies can effectively increase efficiency in CAM processes is discussed.
Originality/value
To the best of our knowledge, no study comprehensively determined the body of existing knowledge on the aspects of digitalization related to the field of continuing airworthiness management and aircraft maintenance. The results of this study provide a positive contribution to airlines, policymakers, manufacturers and maintenance organizations achieving additional benefits from the implementation of digital technologies in the CAM processes.
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This chapter argues that neoliberal governmentality in immunization relocates the Turkish state's position regarding vaccine and immunization policies. Neoliberalism is often…
Abstract
This chapter argues that neoliberal governmentality in immunization relocates the Turkish state's position regarding vaccine and immunization policies. Neoliberalism is often discussed in the context of privatization, performance, and effectiveness separately. However, more attention should be paid to the set of strategies that are employed in public policy processes to manage populations in terms of immunization, while intertwining power with knowledge. Following Foucault's concept of governmentality and taking it further within the context of biopolitics, this chapter focuses on different knowledge practices regarding vaccine and immunization policies in Turkey. In doing so, this case study applies a post-structural analysis to examine vaccine production, vaccine know-how, and immunization policies inscribed in policy documents as a form of knowledge practice. The analysis sheds light on the reflexive transformation of the concept of biopolitics, which is moving from state-oriented knowledge practices toward a neoliberal governmentality of immunization.
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Hande Karadag, Faruk Sahin and Cagri Bulut
In the current study based on the resource-based view (RBV), a three-way interaction model tests the relationships among human and social capital resources, innovation orientation…
Abstract
Purpose
In the current study based on the resource-based view (RBV), a three-way interaction model tests the relationships among human and social capital resources, innovation orientation (IO) and innovation capability in the context of new ventures.
Design/methodology/approach
Hierarchical linear regression modeling presents the linear relations at two decision layers of start-ups, their founders and managers. Data is collected and analyzed from 233 new ventures in Turkey.
Findings
Findings of the two and three-way interaction analyses indicate a positive relationship between human capital and innovation capability when social capital and IO are high; however, the relation turns off when low.
Research limitations/implications
The study extends the previous works on the proposed link between intellectual capital (IC) resources and innovation, by confirming the moderating role of social capital and IO on the positive association between human capital resources and innovation capability.
Practical implications
The results show that for start-up companies, the co-existence of strong social capital and the strategic orientation towards innovation is required for the effective utilization of human capital for generating innovation capability within the organization. Thus, this study highlights the importance of networks, alliances and social relationships, together with the unification of strategic thinking, organizational learning and a culture of innovation for attaining innovation goals, which are crucial for the survival and success of these units.
Originality/value
This study presents the first model in the literature which examines the moderating effects of IO and social capital on the human capital-innovation capability relationship.
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Melisa Ozbiltekin-Pala, Aydın Koçak and Yigit Kazancoglu
COVID-19 is a global event affecting supply chain operations and human health. With COVID-19, many issues in business models, business processes and supply chains, especially in…
Abstract
Purpose
COVID-19 is a global event affecting supply chain operations and human health. With COVID-19, many issues in business models, business processes and supply chains, especially in the manufacturing industry, have had to change. The ability to analyze supply chain performances and ensure circularity in supply chains has become one of the factors whose importance has increased rapidly with COVID-19. Therefore, it aims to determine which supply chain performance criteria come to the fore for the company under consideration to accelerate the transformation into high performance and circularity in supply chains.
Design/methodology/approach
In this study, a new circular-SCOR model is proposed, and 17 supply chain performance measurement criteria are prioritized for a manufacturing company in the context of circular economy principles during COVID-19 by using stepwise weight assessment ratio analysis and analytical hierarchy process method, separately.
Findings
As a result, for both methods, in the case study discussed, the demand fulfillment rate is determined as the most prominent criterion in line with the circular economy principles in the COVID-19 period in manufacturing supply chains.
Originality/value
It is expected that this study will contribute to managers and policy makers as it addresses the “new normal” that started after COVID-19 and the criteria to be considered in supply chain performance measurement and emphasizes the need to adopt circular supply chains, especially in manufacturing industries.
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Emre Yaşar, Mahmut Demir and Turgay Taşdemir
This study aims to examine consumers' purchasing and consumption behavior regarding big data embedded in packaged food post-Covid-19. The second purpose is to determine whether…
Abstract
Purpose
This study aims to examine consumers' purchasing and consumption behavior regarding big data embedded in packaged food post-Covid-19. The second purpose is to determine whether consumer purchasing behavior varies depending on the variety and volume of big data on food packages.
Design/methodology/approach
Semi-structured interviews were conducted to investigate consumer sentiment regarding big embedded data in packaged foods during purchasing. Based on samples from packaged foods sold in international chain stores, interview data collected from 24 participants were subjected to systematic analytical procedures.
Findings
The results revealed that before Covid-19, consumers had positive thoughts about the expiration date, brand, and product contents but did not care much about other data. At the same time, post-Covid-19, there were changes in their attitudes and behaviors on this issue. Post-Covid-19, it has been observed that consumers have positive attitudes and behaviors toward human health and food safety issues regarding unprocessed big data in packaged foods.
Originality/value
This study provides a different perspective on consumer purchasing behavior through big data on packaged foods post-Covid-19. Embedded information in packaged foods provides important data regarding consumer purchasing behavior. As a powerful source of consumer sentiment, this data also provides a reference for consumer purchasing decisions.
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Behnam Hamedi and Alireza Mokhtar
The purpose of this study is to investigate and analysis of energy consumption for this industry. The core part of any energy management system (EnMS) in industry is to perfectly…
Abstract
Purpose
The purpose of this study is to investigate and analysis of energy consumption for this industry. The core part of any energy management system (EnMS) in industry is to perfectly monitor the energy consumption of significant users and to continuously improve the energy performance. In petrochemical plants, production deals with energy-intensive processes, and measuring energy performance for recognition and assessment of potentials for saving is critical.
Design/methodology/approach
The required data are exploited for the period of March 2011-August 2016 (data set: 2,012 days). Multivariate linear regression (MLR) and multi-layer perceptron artificial neural network (ANN) methods are separately used to anticipate the energy consumption. The baseline will be assumed as a reference to be compared with the actual data to estimate the real saving values. Finally, cumulative summations (CUSUM) are proposed and applied as an effective indicator for measurement of energy performance in an LDPE.
Findings
In this study, two statistical methods of MLR and ANN were used to design and develop a comprehensive energy baseline representing the predicted amounts of energy consumption based on the recognized drivers. Although both models imply robust outcomes, when the relative errors are taken into account, performance of ANN models appears fairly superior compared to the MLR model.
Originality/value
It is highly suggested to the ISO technical committee dealing with energy management standards, to consider the proposed model for baseline development in the future version of the standard ISO 50006 as the supplementary extension for the ISO 50001 for measuring energy performance using EnB and EnPI. As for future studies, the research can be extended to investigate the uncertainty and the model could also become completed applying more advanced ANNs such as recurrent neural networks.
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Franck Armel Talla Konchou, Pascalin Tiam Kapen, Steve Brice Kenfack Magnissob, Mohamadou Youssoufa and René Tchinda
This paper aims to investigate the profile of the wind speed of a Cameroonian city for the very first time, as there is a growing trend for new wind energy installations in the…
Abstract
Purpose
This paper aims to investigate the profile of the wind speed of a Cameroonian city for the very first time, as there is a growing trend for new wind energy installations in the West region of Cameroon. Two well-known artificial neural networks, namely, multi-layer perceptron (MLP) and nonlinear autoregressive network with exogenous inputs (NARX), were used to model the wind speed profile of the city of Bapouh in the West-region of Cameroon.
Design/methodology/approach
In this work, the profile of the wind speed of a Cameroonian city was investigated for the very first time since there is a growing trend for new wind energy installations in the West region of Cameroon. Two well-known artificial neural networks namely multi-layer perceptron (MLP) and nonlinear autoregressive network with exogenous inputs (NARX) were used to model the wind speed profile of the city of Bapouh in the West-region of Cameroon. The meteorological data were collected every 10 min, at a height of 50 m from the NASA website over a period of two months from December 1, 2016 to January 31, 2017. The performance of the model was evaluated using some well-known statistical tools, such as root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). The input variables of the model were the mean wind speed, wind direction, maximum pressure, maximum temperature, time and relative humidity. The maximum wind speed was used as the output of the network. For optimal prediction, the influence of meteorological variables was investigated. The hyperbolic tangent sigmoid (Tansig) and linear (Purelin) were used as activation functions, and it was shown that the combination of wind direction, maximum pressure, maximum relative humidity and time as input variables is the best combination.
Findings
Maximum pressure, maximum relative humidity and time as input variables is the best combination. The correlation between MLP and NARX was computed. It was found that the MLP has the highest correlation when compared to NARX.
Originality/value
Two well-known artificial neural networks namely multi-layer perceptron (MLP) and nonlinear autoregressive network with exogenous inputs (NARX) were used to model the wind speed profile.
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Dilvin Taşkın, Gülin Vardar and Berna Okan
The development of green economy is of academic and policy importance to governments and policymakers worldwide. In the light of the necessity of renewable energy to sustain green…
Abstract
Purpose
The development of green economy is of academic and policy importance to governments and policymakers worldwide. In the light of the necessity of renewable energy to sustain green economic growth, this study aims to examine the relationship between renewable energy consumption and green economic growth, controlling for the impact of trade openness for Organization for Economic Co-operation and Development countries over the period 1990-2015, within a multivariate panel data framework.
Design/methodology/approach
To investigate the long-run relationship between variables, panel cointegration tests are performed. Panel Granger causality based on vector error correction models is adopted to understand the short- and long-run dynamics of the data. Furthermore, ordinary least square (OLS), dynamic OLS and fully modified OLS methods are used to confirm the long-run elasticity of green growth for renewable energy consumption and trade openness. Moreover, system generalized method of moment is applied to eliminate serial correlation, heteroscedasticity and endogeneity problems. The authors used the panel Granger causality test developed by Dumitrescu and Hurlin (2012) to infer the directionality of the causal relationship, allowing for both the cross-sectional dependence and heterogeneity.
Findings
The results suggest that renewable energy consumption and trade openness exert positive effects on green economic growth. The results of long-run estimates of green economic growth reveal that the long-run elasticity of green economic growth for trade openness is much greater than for renewable energy consumption. The estimated results of the Dumitrescu and Hurlin (2012) test reveal bidirectional causality between green economic growth and renewable energy consumption, providing support for the feedback hypothesis.
Practical implications
This paper provides strong evidence of the contribution of renewable energy consumption on green economy for a wide range of countries. Despite the costs of establishing renewable energy facilities, it is evident that these facilities contribute to the green growth of an economy. Governments and public authorities should promote the consumption of renewable energy and should have a support policy to promote an active renewable energy market. Furthermore, the regulators must constitute an efficient regulatory framework to favor the renewable energy consumption.
Social implications
Many countries focus on increasing their GDP without taking the environmental impacts of the growth process into account. This paper shows that renewable energy consumption points to the fact that countries can still increase their economic growth with minimal damage to environment. Despite the costs of adopting renewable energy technologies, there is still room for economic growth.
Originality/value
This paper provides evidence on the contribution of renewable energy consumption on green economic growth for a wide range of countries. The paper focuses on the impact of renewable energy on economic growth by taking environmental degradation into consideration on a wide scale of countries.