scholarly journals A Study on the Validation of Green Supply Chain Performance Measures in the Automotive Industry

2011 ◽  
pp. 1-14 ◽  
Author(s):  
Ezutah Olugu ◽  
Kuan Wong
Keyword(s):  
Supply Chain ◽  
Performance Measures ◽  
Automotive Industry ◽  
Green Supply Chain ◽  
Supply Chain Performance

scholarly journals Green supply chain performance measures: A review and bibliometric analysis

2017 ◽  
Vol 10 ◽  
pp. 85-99 ◽  
Author(s):  
Deepa Mishra ◽  
Angappa Gunasekaran ◽  
Thanos Papadopoulos ◽  
Benjamin Hazen
Keyword(s):  
Supply Chain ◽  
Bibliometric Analysis ◽  
Performance Measures ◽  
Green Supply Chain ◽  
Supply Chain Performance

Green Supply Chain Integration in Automotive Industry

2015 ◽  
pp. 5056-5064 ◽  
Author(s):  
Joey Soo Yee Phuah ◽  
Yudi Fernando
Keyword(s):  
Supply Chain ◽  
Automotive Industry ◽  
Supply Chain Integration ◽  
Green Supply Chain ◽  
Supply Chain Performance ◽  
Material Flows ◽  
Business World ◽  
Environmentally Sustainable ◽  
Environmentally Responsible ◽  
Activity Information

Since the last decade, the business world is fully conscious about the environmental problems and green products for sustainable development. This fact has been seriously considered in the automotive industry supply chain where the company and its associate suppliers are socially and environmentally responsible. Hence, green supply chain has emerged as a key approach for automotive industry to become environmentally sustainable and supply chain integration becomes a vital contributor to supply chain performance and the firm competitiveness. This chapter has reviewed refereed articles related to the topic. This is used as a basis to conceptualize green supply chain integration in the automotive industry. Therefore, there are a growing need to discuss further on internal and external integration including the activity, information technology and logistic integration. This chapter will also discuss on the integrations of both information and material flows between supply chain partners and the effect on operational performance and competitiveness in automotive industry.

scholarly journals Green Supply Chain Performance Prediction Using a Bayesian Belief Network

2020 ◽  
Vol 12 (3) ◽  
pp. 1101 ◽  
Author(s):  
Md. Rabbi ◽  
Syed Mithun Ali ◽  
Golam Kabir ◽  
Zuhayer Mahtab ◽  
Sanjoy Kumar Paul
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Performance Measures ◽  
Performance Indicators ◽  
Bayesian Belief Network ◽  
Sustainable Growth ◽  
Green Supply Chain ◽  
Supply Chain Performance ◽  
Belief Network ◽  
The Impact

Green supply chain management (GSCM) has emerged as an important issue to lessen the impact of supply chain activities on the natural environment, as well as reduce waste and achieve sustainable growth of a company. To understand the effectiveness of GSCM, performance measurement of GSCM is a must. Monitoring and predicting green supply chain performance can result in improved decision-making capability for managers and decision-makers to achieve sustainable competitive advantage. This paper identifies and analyzes various green supply chain performance measures and indicators. A probabilistic model is proposed based on a Bayesian belief network (BBN) for predicting green supply chain performance. Eleven green supply chain performance indicators and two green supply chain performance measures are identified through an extensive literature review. Using a real-world case study of a manufacturing industry, the methodology of this model is illustrated. Sensitivity analysis is also performed to examine the relative sensitivity of green supply chain performance to each of the performance indicators. The outcome of this research is expected to help managers and practitioners of GSCM improve their decision-making capability, which ultimately results in improved overall organizational performance.

Developing and Implementing a Port Fluidity Performance Measurement Methodology using Automatic Identification System Data

2018 ◽  
Vol 2672 (11) ◽  
pp. 30-40 ◽  
Author(s):  
C. James Kruse ◽  
Kenneth N. Mitchell ◽  
Patricia K. DiJoseph ◽  
Dong Hun Kang ◽  
David L. Schrank ◽  
...  
Keyword(s):  
Supply Chain ◽  
Travel Time ◽  
Performance Measures ◽  
Automatic Identification ◽  
Identification System ◽  
Army Corps ◽  
Supply Chain Performance ◽  
Travel Time Reliability ◽  
Automatic Identification System ◽  
The U.S

The U.S. Army Corps of Engineers (USACE) is responsible for the maintenance of federally authorized navigation channels and associated infrastructure. As such, USACE requires objective performance measures for determining the level of service being provided by the hundreds of maintained navigation projects nationwide. To this end, the U.S. Army Engineer Research and Development Center partnered with Texas A&M Transportation Institute to develop a freight fluidity assessment framework for coastal ports. The goal was to use archival automatic identification system (AIS) data to develop and demonstrate how ports can be objectively compared in relation to fluidity, or the turnaround time reliability of oceangoing vessels. The framework allows USACE to evaluate maintained navigation project conditions alongside port system performance indices, thereby providing insight into questions of required maintained channel dimensions. The freight fluidity concept focuses on supply chain performance measures such as travel time reliability and end-to-end shipping costs. Although there are numerous research efforts underway to implement freight fluidity, this is the first known application to U.S. ports. This paper covers AIS data inputs, quality control, and performance measures development, and also provides a demonstration application of the methodology at the Port of Mobile, Alabama, highlighting travel time and travel time reliability operating statistics for the overall port area. This work provides foundational knowledge to practitioners and port stakeholders looking to improve supply chain performance and is also valuable for researchers interested in the development and application of multimodal freight fluidity performance measures.

A New Approach to Supply Chain Performance Measurement

2016 ◽  
pp. 111-128
Author(s):  
Amit Kumar Marwah ◽  
Girish Thakar ◽  
R. C. Gupta
Keyword(s):  
Factor Analysis ◽  
Supply Chain ◽  
Performance Measures ◽  
Research Work ◽  
Primary Data ◽  
Supply Chain Performance ◽  
New Approach ◽  
Factors Affecting ◽  
Manufacturing Organizations ◽  
Overall Reliability

Existing research work has established that many of today's manufacturing organizations have failed to develop a comprehensive supply chain performance measures. In this chapter, the authors intend to empirically assess the effects of supplier buyer relations and human metrics on supply chain performance in the context of Indian manufacturing organizations. After rigorous literature review, total 18 variables have been identified which are later on reduced in number by factor analysis. As a pilot study, primary data is collected from 100 manufacturing organizations by means of a questionnaire and a scale is developed. On a sample size of 100, the proposed hypotheses are tested by applying two-tailed tests. t-test and factor analysis resulted in 5 factors, 2 related to supplier-buyer relations and 3 related to human metrics. The overall reliability of the scale comes out to be 0.697. The research work provides a new approach to the manufacturing organizations to understand the factors affecting supply chain performance. The present study is limited to Indian manufacturing organizations.

scholarly journals Effect of IoT Capabilities and Energy Consumption behavior on Green Supply Chain Integration

2018 ◽  
Vol 8 (12) ◽  
pp. 2481 ◽  
Author(s):  
Muhammad Shafique ◽  
Ammar Rashid ◽  
Imran Bajwa ◽  
Rafaqat Kazmi ◽  
Muhammad Khurshid ◽  
...  
Keyword(s):  
Supply Chain ◽  
Energy Consumption ◽  
Survey Methods ◽  
Partial Least Square ◽  
Supply Chain Integration ◽  
Green Supply Chain ◽  
Equation Modeling ◽  
Supply Chain Performance ◽  
Consumption Behavior ◽  
Supplier Integration

The Internet of Things (IoT) is the next generation of internet-connected information communication technologies (ICT). IoT typically integrates supply chain activities to enhance green supply chain performance (GSCP). Since every organization has different IoT capabilities in comparison with other organizations, GSCP can enable supply chain integration activities for enhanced performance. The implementation of an IoT system can reduce the consumption of organizational resources like energy, electricity, and time and can increase the operational speed to gain better logistics and, ultimately, improved supply chain performance. This study has developed and empirically tested the relationship between IoT capabilities, energy consumption behavior (ECB), supply chain integration, green training (GT), and supply chain practices. Such a multidisciplinary relationship has not previously been established in the literature. The proposed study can fulfill the literature gap and opens new horizons for interdisciplinary research. Data used in this study are collected through offline and online survey methods. A total number of 250 out of 400 respondents participated in the survey. Data has been analyzed through partial least square—structure equation modeling (PLS—SEM) technique. The results of this study empirically test the developed model. IoT has a positive effect on supplier integration (SI), and customer integration (CI). Furthermore, SI and CI have a mediating role between IoT and GSCP, and GT has a positive impact on GSCP. It is concluded that the implementation of IoT can integrate CI and SI to increase GSCP. GT and ECB can ultimately improve GSCP. Additionally, the use of technology and GT can motivate employees to save energy and protect the environment to increase GSCP.

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