Interpretive Structural Modeling Analysis of Reverse Supply Chain Critical Success Factors in Air Industry

Adabavazaeh, Nazila; Nikbakht, Mehrdad

doi:10.1109/iiiec.2019.8720737

Cited by 8 publications

(8 citation statements)

References 66 publications

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“…Moreover, this research used ISM as the research design. Most of the previous research used ISM for the production process categorized as an engineering field (Adabavazaeh and Nikbakht, 2019;Euchi et al, 2019;Kaswan and Rathi, 2019;Huang et al, 2020;Yang and Lin, 2020). And on the disaster field, there are several researches using ISM but could not address Indonesia's need as a disaster-prone area (Jahantigh and Jannat, 2019;Mercado et al, 2019).…”

Section: Classification Of Sub-elementsmentioning

confidence: 99%

The obstacles hierarchy of school disaster preparedness implementation in Mount Sinabung area, Indonesia

et al. 2022

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The incidence of natural disasters has an impact on various sectors of life, including the education sector. Schools as educational facilities are considered vulnerable areas that need handling steps to reduce disaster risk. As one of the most vulnerable countries to natural disasters, Indonesia already has several policies and programs from the government to address these problems. However, several studies have shown that the implementation did not go according to plan. These studies also reveal that this implementation lies in the local context in which the program or policy is implemented. That is why the study aims to examine the school disaster preparedness implementation in the Mount Sinabung area as one of the disaster-prone areas in Indonesia. This research utilizes the Interpretative Structural Modeling approach to build a hierarchy and classification of obstacles in implementing school disaster preparedness around that area. Data are collected through a combination of observation, interview, and survey techniques in 2017 and 2018 that involved a total of 35 participants. The result showed 14 sub-elements identified as limiting factors of school preparedness implementation in the Mount Sinabung area. Three elements serve as the first level (or the basis/key element) of the obstacles hierarchy: Integration of subject, school policy, and school curriculum. Intervention at the base level will trigger changes and give impact the other upper-four levels of elements. This hierarchy and classification are relevant to the context of the Mount Sinabung eruption and cannot be applied in other areas. This research did not measure the numeric data per sub-element in disaster preparedness. Therefore, the limitations of this study can be directions for future research to examine the implementation in another area by using numeric data. The results of this study also provide major recommendations to several stakeholders. The existing policies regarding school disaster preparedness and their implementation need to be reviewed to improve the result.

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Section: Classification Of Sub-elementsmentioning

confidence: 99%

The obstacles hierarchy of school disaster preparedness implementation in Mount Sinabung area, Indonesia

et al. 2022

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“…Examining the literature review, we found that previous studies in the field of RL have been conducted on several key topics; namely, RL network design (Yan and Yan (2019); Zarbakhshnia et al , 2019; Liao, 2018; John et al , 2018; Alshamsi and Diabat, 2017; Yu and Solvang, 2016; Kilic et al , 2015); Model for the evaluation of RL performance (Hammes et al , 2020; Kazancoglu et al , 2020; Chaves et al , 2020; Han and Trimi, 2018; Peña-Montoya et al , 2020); Investigation of critical success factors in RL implementation (Chakraborty et al , 2018; Adabavazaeh and Nikbakht, 2019; Mangla et al , 2016); Identification of different options in RL and choosing the best option (Wang et al , 2019; Agrawal et al , 2016); RL for sustainability (Asees and Ali, 2019; Agrawal and Singh, 2019); Investigation of the barriers to RL implementation (Sirisawat and Kiatcharoenpol, 2018; Ali et al , 2018; Bouzon et al , 2018; Prakash and Barua, 2016; Bouzon et al , 2016; Bouzon et al , 2016a) and few studies in supply chain management and RL have been conducted using Twitter social media data (Schmidt et al , 2020; Sharma et al , 2020; Tseng et al , 2019; Iftikhar and Khan, 2018; Singh et al , 2018; Mishra et al , 2017; Chan et al , 2016; Chae, 2015; He et al , 2013). We also found that research on the use of customer feedback in RL decisions is very limited (Mishra et al , 2017).…”

Section: Discussion and Implicationmentioning

confidence: 99%

“…Chakraborty et al (2018) developed a causal model among the identified issues and sub-issues for setting up a reverse supply chain in an Indian semiconductor manufacturing industry and then they evaluated the critical issues based on the causal relations. Adabavazaeh and Nikbakht (2019) analysed reverse supply chain critical success factors in the air industry using ISM. Ravi and Shankar (2017) analysed the interaction among major variables of RL seen in automobile industries.…”

Section: Literature Reviewmentioning

confidence: 99%

A mixed-method approach for modelling customer-centric mobile phone reverse logistics: application of social media data

Shokouhyar

Dehkhodaei

Amiri

2021

JM2

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Purpose Recently, reverse logistics (RL) has become more prominent due to growing environmental concerns, social responsibility, competitive advantage and high efficiency by customers because of the expansion of product selection and shorter product life cycle. However, effective implementation of RL results in some direct advantages, the most important of which is winning customer satisfaction that is vital to a firm’s success. Therefore, paying attention to customer feedback in supply chain and logistics processes has recently increased so that manufacturers have decided to transform their RL into customer-centric RL. Hence, this paper aims to identify the features of a mobile phone which affect consumer purchasing behaviour and to analyse the interrelationship among them to develop a framework for customer-centric RL. These features are studied based on website analysis of several mobile phone manufacturers. The special focus of this paper is on social media data (Twitter) in an attempt to help the decision-making process in RL through a big data analysis approach. Design/methodology/approach A portfolio of mobile phone features that affect consumer’s mobile phone purchasing decisions has been taken from website analysis by several mobile phone manufacturers to achieve this objective. Then, interrelationships between the identified features have been established by using big data supplemented with interpretive structural modelling (ISM). Apart from that, cross-impact matrix multiplication, applied to classification analysis, was carried out to graphically represent these features based on their driving power and dependence. Findings During the study, it has been observed from the ISM that the chip (F5) is the most significant feature that affects customer’s buying behaviour; therefore, mobile phone manufacturers realize that this is to be addressed first. Originality/value The focus of this paper is on social media data (Twitter) so that experts can understand the interaction between mobile phone features that affect consumer’s decisions on mobile phone purchasing by using the results.

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“…Adabavazaeh and Nikbakht [14] apply Lawshe's method and 11 professional experts to proposed the CSFs of the aviation industry, including customer service and satisfaction, financial management, technology, environmental awareness of supply chain, inventory management, transportation, materials, professional technology, supply chain partner mutual trust, knowledge management, operation standardization, return collection, and return monitoring system.…”

Section: Discussion On Industrial Literaturementioning

confidence: 99%

“…With the emphasis on competitiveness, the implementation of reverse logistics in enterprises has received considerable attention [10,11]. Taiwan's electronic products are sold all over the world, but with the WEEE Directive, EUP, and RoHS of the EU, reverse logistics management can reduce pollution, save money, increase revenue, and improve companies' competitive advantages [8,[11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

A Survey of Critical Success Factors in the Implementation of Reverse Logistics in Taiwan’s Optoelectronic Industry

2020

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With increasing global awareness of environmental issues, international environmental protection policies and regulations have been enacted. Many enterprises have manufactured the products or required their suppliers to meet international standards to gain business opportunities and maintain competitiveness. Hence, the green investment, reverse logistics management, control and corporate responsibilities, and increasing profit and reducing operating costs ensure that enterprises' competitive advantages are central to enterprise management. In this study, literature analysis and experts survey were adopted, and questionnaires were administered to three optoelectronic enterprises and experts, to calculate the weights of all critical success factors and thus analyze the important reasons. The study results are as follows. To establish the optoelectronic industry and introduce reverse logistics, there are five dimensions: economic cost, customer cost, environmental protection need, green need, and social responsibility. The weights of the dimensions are arranged in order: economic cost (0.363), customer cost (0.268), environmental protection need (0.163), green need (0.112), and social responsibility (0.095). In addition, there are 17 evaluation indexes.

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Interpretive Structural Modeling Analysis of Reverse Supply Chain Critical Success Factors in Air Industry

Cited by 8 publications

References 66 publications

The obstacles hierarchy of school disaster preparedness implementation in Mount Sinabung area, Indonesia

The obstacles hierarchy of school disaster preparedness implementation in Mount Sinabung area, Indonesia

A mixed-method approach for modelling customer-centric mobile phone reverse logistics: application of social media data

A Survey of Critical Success Factors in the Implementation of Reverse Logistics in Taiwan’s Optoelectronic Industry

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