SCOR based key success factors in cooking oil supply chain buyers perspective in Padang City

2017 ◽  
Author(s):  
Fatimah Zahara ◽  
Rika Ampuh Hadiguna
Keyword(s):  
Supply Chain ◽  
Success Factors ◽  
Key Success Factors ◽  
Oil Supply ◽  
Cooking Oil

Third Party Logistics

2011 ◽  
Vol 2 (4) ◽  
pp. 29-60 ◽  
Author(s):  
Omprakash K. Gupta ◽  
S. Samar Ali ◽  
Rameshwar Dubey
Keyword(s):  
Supply Chain ◽  
Success Factors ◽  
Third Party ◽  
Third Party Logistics ◽  
Growth Strategies ◽  
Chain Management ◽  
Key Success Factors ◽  
Critical Success ◽  
The World ◽  
Academic Professionals

Third party logistics (3PL) has been gaining importance in most places in the world. In India the implementation of 3PL practices has made its beginning and it is emerging as one of the fastest growing sectors. It is still a relatively new concept and not well understood among industry or academic professionals in India. This paper examines the Indian 3PL Supply Chain Management and practices with respect to the key success factors and growth strategies. After identifying the critical success factors SERVQUAL is applied to reveal the gap between their achievement and expectation. Respondents to the survey are categorized based on their rating of the key growth strategies on the basis of AHP.

Who is the most effective stakeholder to incent in the waste cooking oil supply chain? A case study of Beijing, China

2019 ◽  
Vol 4 (3) ◽  
pp. 116-124 ◽  
Author(s):  
Tingting Liu ◽  
Yaru Liu ◽  
Enhua Luo ◽  
Yufeng Wu ◽  
Yong Li ◽  
...  
Keyword(s):  
Supply Chain ◽  
Waste Cooking Oil ◽  
Oil Supply ◽  
Cooking Oil ◽  
Beijing China

A global exploration of Big Data in the supply chain

2016 ◽  
Vol 46 (8) ◽  
pp. 710-739 ◽  
Author(s):  
Robert Glenn Richey ◽  
Tyler R. Morgan ◽  
Kristina Lindsey-Hall ◽  
Frank G. Adams
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Operations Management ◽  
Success Factors ◽  
Future Research ◽  
Chain Management ◽  
Content Type ◽  
Key Success Factors ◽  
Starting Point

Purpose Journals in business logistics, operations management, supply chain management, and business strategy have initiated ongoing calls for Big Data research and its impact on research and practice. Currently, no extant research has defined the concept fully. The purpose of this paper is to develop an industry grounded definition of Big Data by canvassing supply chain managers across six nations. The supply chain setting defines Big Data as inclusive of four dimensions: volume, velocity, variety, and veracity. The study further extracts multiple concepts that are important to the future of supply chain relationship strategy and performance. These outcomes provide a starting point and extend a call for theoretically grounded and paradigm-breaking research on managing business-to-business relationships in the age of Big Data. Design/methodology/approach A native categories qualitative method commonly employed in sociology allows each executive respondent to provide rich, specific data. This approach reduces interviewer bias while examining 27 companies across six industrialized and industrializing nations. This is the first study in supply chain management and logistics (SCMLs) to use the native category approach. Findings This study defines Big Data by developing four supporting dimensions that inform and ground future SCMLs research; details ten key success factors/issues; and discusses extensive opportunities for future research. Research limitations/implications This study provides a central grounding of the term, dimensions, and issues related to Big Data in supply chain research. Practical implications Supply chain managers are provided with a peer-specific definition and unified dimensions of Big Data. The authors detail key success factors for strategic consideration. Finally, this study notes differences in relational priorities concerning these success factors across different markets, and points to future complexity in managing supply chain and logistics relationships. Originality/value There is currently no central grounding of the term, dimensions, and issues related to Big Data in supply chain research. For the first time, the authors address subjects related to how supply chain partners employ Big Data across the supply chain, uncover Big Data’s potential to influence supply chain performance, and detail the obstacles to developing Big Data’s potential. In addition, the study introduces the native category qualitative interview approach to SCMLs researchers.

scholarly journals FAKTOR KUNCI KEBERHASILAN MANAJEMEN RANTAI PASOKAN PENANGANAN BENCANA ALAM DALAM PERSPEKTIF PEMERINTAH

2020 ◽  
Vol 10 (1) ◽  
pp. 62
Author(s):  
Poppy Laksita Rini
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Inventory Management ◽  
Qualitative Methodology ◽  
Success Factors ◽  
Chain Management ◽  
Key Success Factors ◽  
Team Assessment ◽  
The Government ◽  
High Level

Disaster supply chain management is different from the supply chain management of commercial organization because of the high level of uncertainty. The high level of uncertainty significantly affects the availability of logistic supplies that are  needed  by the victims of the disaster. This study discovers the key success factors of the disaster supply chain management based on the perspective of the government. The re- search specifically study the Government of the D.I. Yogyakarta that are represented by Badan Penanggulangan Bencana Daerah (BPBD). Due the fact that Yogyakarta as one of the regions that have the high risk of catastrophic nature in Indonesia. The study will be carried out in a qualitative methodology by conducting deep interview with the Representative of Logistics Department in BPBD. The results of in-depth interviews with four representative of BPBD found that there are six key success factors of disasater management supply chain management which are : (1) Quality of the TRC Team Assessment Results; (2) BPBD Coordination with Government and Non-Government; (3) Effective Rules and Regulations; (4) Character and Attitude of the Community in Dealing with Disasters; (5) BPBD Warehouse Inventory Management; (6) Management Information Systems and Data Updates.

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