scholarly journals PENGEMBANGAN MODEL PENGUKURAN KINERJA RANTAI PASOK PADA INDUSTRI KONSTRUKSI PERUMAHAN SEDERHANA

2019 ◽  
Vol 9 (1) ◽  
pp. 48-53
Author(s):  
Putranesia ◽  
Taufika Ophiyandri ◽  
Yervi Hesna
Keyword(s):  
Supply Chain ◽  
Asset Management ◽  
Supply Chain Performance ◽  
Supply Chain Costs ◽  
Target Program

Kebutuhan akan tempat tinggal masyarakat yang semakin tinggi, mendorong dilaksanakannya program sejuta rumah oleh pemerintah yang dimulai tahun 2015. Pada tahun 2016 target program sejuta rumah terdiri dari 700.000 unit untuk masyarakat berpenghasilan rendah (MBR) dan 300.000 unit lainnya untuk non-MBR (Ditjen PUPR,2016). Kondisi ini mendorong munculnya para pengembang baru yang ikut aktif dalam mengembangkan perumahan sederhana. Konsumen sebagai pemilik akhir dari sebuah produk industri perumahan seringkali mendapatkan permasalahan dari para pengembang. Permasalahan yang timbul seperti: (a) kontruksi bangunan yang tidak memenuhi kaidah-kaidah konstruksi yang benar (tidak memenuhi SNI), (b) infrastruktur yang tidak memadai, (c) tenggang waktu penyelesaian bangunan yang tidak sesuai jadwal yang disepakati, (d) pemahaman konsumen yang kurang akan produk perumahan yang berkwalitas membuat rentan untuk di manipulasi pengembang. Dalam penelitian ini akan dilakukan sebuah pengukuran kinerja dengan menggunakan metoda SCOR® versi 11 pada industri konstruksi perumahan sederhana. responsiveness dan efficiency merupakan karakteristik yang dapat menggambarkan kinerja rantai pasok yang bersifat dinamis sehingga mampu menyesuaikan setiap perubahan yang terjadi pada pasokan dan permintaan. Harmonisasi  antara kinerja dan manajemen rantai pasok diawali dengan menghitung atribut dan metrik kinerja,menentukan bobot metric kinerja dengan pendekatan AHP,menentukan performansi atribut supply chain performance sehingga didapatkan nilai supply chain performance : reliability 0.205, responsiveness 0.107, Agility 0.130, Supply Chain Costs 0.040, dan Supply Chain Asset Management 0.015.

Supply chain performance measurement for third party logistics

2014 ◽  
Vol 21 (6) ◽  
pp. 944-963 ◽  
Author(s):  
Dhanya Jothimani ◽  
S.P. Sarmah
Keyword(s):  
Supply Chain ◽  
Performance Measurement ◽  
Asset Management ◽  
Real Life ◽  
Integrated Approach ◽  
Third Party ◽  
Supply Chain Performance ◽  
Third Party Logistics ◽  
Content Type ◽  
Scor Model

Purpose – The purpose of the paper is to explore the applicability of the Supply Chain Operations Reference (SCOR) model and to identify the key performance indicators (KPIs) for the service-oriented sector – namely a third-party logistics (3PL) service provider. Design/methodology/approach – The performance attributes of SCOR model (reliability, responsiveness, flexibility, cost measures and asset management efficiency) are used as the basis for defining the KPIs. A questionnaire was sent to relevant decision makers. Findings – This paper illustrates the use of the integrated approach of SCOR, fuzzy analytic hierarchy process (FAHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for measuring the supply chain performance (SCP) in the light of a real life case study company. Research limitations/implications – This method forms the basis for performance measurement using the SCOR model to evaluate strategy. In this work, the performance of the company has been compared with its own previous performance. The work can be extended to external benchmarking and also to other sectors. Practical implications – The paper attempts to overcome the conflict between the top-down strategy and bottom-up implementation process. The paper links the strategic objective with operations which would aid managers at different levels of an organization with decision making. The KPIs, when implemented in a business intelligence (BI) tool, would result in real time performance measurement. Originality/value – The paper focusses on 3PLs. It provides a base for measuring the SCP using SCOR model. The paper also identified KPIs for three domains of 3PL, namely freight forwarding, customs and warehousing.

Impact of metric-alignment on supply chain performance: a behavioral study

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Arunachalam Narayanan ◽  
Rafay Ishfaq
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Bullwhip Effect ◽  
Supply Chain Performance ◽  
Behavioral Study ◽  
Managerial Decision ◽  
Managerial Decision Making ◽  
New Approach ◽  
Content Type ◽  
Supply Chain Costs

PurposePrevious research has shown that firms are struggling to incorporate collaboration among supply chain partners. This paper presents a new approach to incorporate collaboration using metric-alignment. The analysis provides key insights regarding the usefulness of this approach to synchronize decision-making that leads to reduced bullwhip effect, less backordering and lower supply chain costs.Design/methodology/approachThis research is based on a large-scale behavioral study comprising 556 participants in multi-echelon supply chain games. Supply chain decisions from these experiments are evaluated to study the impact of metric-alignment on managerial decision-making and the corresponding effects on the overall supply chain performance.FindingsResults show that the metric-alignment approach offers an informal and self-enforced governance mechanism that changes managerial decision-making behaviors and improves supply chain performance. Results also show this approach to yield operational and financial benefits for all supply chain partners in the form of reduced bullwhip effect, less backordering and lower supply chain costs.Originality/valueThis is the first behavioral study of its kind that evaluates a new approach to incorporate collaboration in supply chains using metric-alignment. This approach avoids the shortcomings of current industry practices of using monetary penalties, such as on-time in-full (OTIF) mandates in supply contracts. The study shows that metric-alignment approach can improve overall supply chain performance while offering mutually beneficial rewards for all supply chain partners.

scholarly journals ANALISIS RANTAI PASOK AGROINDUSTRI TEMPE DI KELURAHANGUNUNG SULAH KECAMATAN WAY HALIM KOTA BANDAR LAMPUN

2020 ◽  
Vol 8 (4) ◽  
pp. 633
Author(s):  
Zauvi Natasena Ajusa ◽  
Zainal Abidin ◽  
Eka Kasymir
Keyword(s):  
Supply Chain ◽  
Asset Management ◽  
Direct Marketing ◽  
Sampling Technique ◽  
Flow Patterns ◽  
Supply Chain Performance ◽  
Snowball Sampling ◽  
Supply Chain System ◽  
Street Vendors ◽  
Marketing Efficiency

This study aims to figure out the flow patterns and stakeholders of, supply chain performance of, and marketing efficiency of tempe agroindustry. Data collection was conducted in Gunung Sulah Subdistrict, Way Halim District, Bandar Lampung City from December 2018 to January 2019. This study uses a casestudy method. Determination of agroindustry sample uses purposive sampling technique and for supply chain sample uses snowball sampling technique. The data analysis method used for flow patterns and stakeholders are the supply chain system method, for the analysis of supply chain performance is SupplyChain Operation Reference (SCOR) 9.0 and for marketing efficiency analysis is the calculation of margin value, and the value of producer's share. The results of this study showed that supply chain of tempe agroindustry consisted of soybean importer, soybean agent, yeast and plastic wholesaler, soybean, yeast and plastic retailers, sub-agent of gas, producer of firewood, tempe’s agroindustries, tempe retailers, and street vendors. There is an inefficiency in cost management of Cost of Goods Sold (COGS) metric for tempe products of tempe’s agroindustry and asset management of Cash to Cash Cycle Time (CTCCT) metric for soybean, yeast, and fuel supply of tempe’s agroindustry. The most efficient marketing of tempe’s agroindustry is direct marketing to consumers with margin value of zero and producer’s share value of 100%.Key words: margin, marketing, producer’s share, supply chain, SCOR

scholarly journals RELATIONSHIP BETWEEN HEDGING RISK MANAGEMENT STRATEGY AND SUPPLY CHAIN PERFORMANCE AMONG MANUFACTURING COMPANIES IN KENYA

2017 ◽  
Vol 1 (2) ◽  
pp. 82
Author(s):  
Dr.David Kiarie ◽  
Dr. Patrick Ngugi ◽  
Dr. Kennedy Ogollah
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Sample Size ◽  
Lead Time ◽  
Management Strategy ◽  
Supply Chain Performance ◽  
Manufacturing Companies ◽  
Risk Management Strategy ◽  
Cycle Times ◽  
Supply Chain Costs

Purpose: The purpose of this study was to determine therelationship between hedging risk management strategy and supply chain performance among manufacturing companies in KenyaMethodology:The study adopted a cross-section survey of descriptive nature .The target population comprised of the 412 manufacturing companies within Nairobi County that were registered members of KAM. The fisher et al formula for calculating the sample size was used to yield a sample size of199. Data was collected using questionnaires and analyzed using statistical package of social sciences (SPSS) version 21 as a tool of analysis.Results: The study findings revealed that the companies that increased buffer stock at various levels in the supply chain. Increasing buffer stock at various levels in the supply chain resulted to decreased lead time, improved quality and reduced cost. Results also showed that most of the companies ‘conducted reduce order cycle times. Conducting reduce order cycle times resulted to decreased lead time, improved quality and reduced cost. Further, the results revealed that most of the companies shared supply chain costs with partners. Sharing supply chain costs with partners resulted to decreased lead time, improved quality and reduced cost.Policy recommendation:the study recommended that manufacturing companies should put in place a risk analysis and evaluation management strategy to enhance supply chain performance. In particular, companies should consider conducting whole life costing of suppliers and also internal quality of suppliers.

Impact of Supply Chain Performance on Firms’ Export Capability: Development of a Statistical Model

2021 ◽  
pp. 097215092110443
Author(s):  
Bijoy Talukder ◽  
Saswati Tripathi
Keyword(s):  
Supply Chain ◽  
Statistical Model ◽  
Asset Management ◽  
Fixed Effects ◽  
Export Performance ◽  
Block Design ◽  
Raw Material ◽  
Supply Chain Performance ◽  
Export Intensity ◽  
Export Competitiveness

The purposes of this article are to establish the crucial indicators of supply chain performance (SCPI) impacting firms’ export performance, revealing its unique characteristics, and assess the effects of these SCPIs on the export capability of the firms. This article develops a statistical model, involving how critical SCPIs can influence firms’ export performance. The developed model is then empirically validated using top 53 firm-level data, based on market share, from the Indian pharmaceutical industry, taken for 10 years. The randomized complete block design approach is employed to confirm the variation of export intensity across firms and time. A panel data fixed-effects model is developed, associating critical SCPIs with export intensity to understand their impact on export performance. Finally, bootstrap is applied as a cross-validation procedure to carry out model authentication. This article contributes to obtaining crucial SCPIs and their impact on firms’ export competitiveness. It has revealed that firms’ raw material import efficiency, working capital efficiency, asset management efficiency, research and development (R&D) capability, and the total cost to serve have a significant impact on the firms’ export capability. The proposed model can help firms make appropriate decisions about different influencing parameters of supply chain performance to improve their export competitiveness.

scholarly journals Framework pengukuran kinerja rantai pasok industri kemasan plastik menggunakan metode SCOR-AHP

2021 ◽  
Vol 13 (2) ◽  
pp. 183
Author(s):  
Deky Aryanto ◽  
Sawarni Hasibuan
Keyword(s):  
Supply Chain ◽  
Performance Measurement ◽  
Asset Management ◽  
Manufacturing Industry ◽  
Performance Indicator ◽  
Supply Chain Performance ◽  
Plastic Packaging ◽  
Measurement Framework ◽  
Packaging Industry ◽  
Level Of Importance

The manufacturing industry in general cannot be separated from the role of the plastic industry. In Indonesia, there are 925 companies that produce various kinds of plastic products for the food and beverage industry, automotive industry, pharmaceutical industry and other industries. Companies are faced with challenges to improve their supply chain competitiveness, while plastic packaging companies generally do not have a comprehensive performance measurement framework in their supply chains. The purpose of this research is to select and determine the level of importance of the Key Performance Indicator (KPI) for measuring the supply chain performance of the plastic packaging industry using the SCOR and AHP framework. In the initial stage, 45 KPIs were identified, from the results of expert validation, 29 KPIs were distributed to the dimensions of reliability, responsiveness, flexibility, cost, and assets. At the level 1 hierarchy the greatest level of importance is generated in the dimensions of reliability (A1), asset management (E1), responsiveness (B1), cost (D1), and flexibility (C1) with weights of 0.262, 0.209, respectively. 0.191, 0.175, and 0.163. The largest distribution of KPIs is on the reliability dimension, namely 32%, followed by the cost dimension of 16%, 12% responsiveness, flexibility and asset management have the same distribution, namely 4%. Based on the results of weighting using the AHP method, a supply chain performance measurement framework is recommended in the case of the plastic packaging industry.

Development of IoT based data-driven agriculture supply chain performance measurement framework

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sanjeev Yadav ◽  
Dixit Garg ◽  
Sunil Luthra
Keyword(s):  
Supply Chain ◽  
Performance Measurement ◽  
Asset Management ◽  
Business Processes ◽  
Fuzzy Topsis ◽  
Data Driven ◽  
Supply Chain Performance ◽  
Content Type ◽  
Measurement Framework ◽  
Level 2

PurposePerformance measurement (PM) of any supply chain is prerequisite for improving its competitiveness and sustainability. This paper develops a framework for supply chain performance measurement (SCPM) for agriculture supply chain (ASC) based on internet of things (IoT). Moreover, this article explains the role of IoT in data collection and communication (SC visibility) based on the supply chain operation reference (SCOR) model.Design/methodology/approachThis research identifies various key performance indicators (KPIs) and also their role in SCPM for improving its sustainability by using SCOR. Further, Shannon entropy is utilized for weighing the basic processes of SCPM and by using weights, fuzzy TOPSIS is applied for ranking of identified KPIs at metrics level 2 (deeper level).Findings“Flexibility” and “Responsiveness” have been reported as two most important KPIs in IoT based SCPM framework for ASC towards achieving sustainability.Research limitations/implicationsIn this research, metrics are explained only at SCOR level 2. But, this research will guide the managers and practitioners of various organizations to set their benchmark for comparing their performance at different levels of business processes. Further, this paper has managerial implications to develop an effective system for PM of IoT based data-driven ASC.Originality/valueBy using IoT based data driven system, this article fills the gap between SCPM by measuring different SC strategies in their performance measurable form of reliable, responsive and asset management etc.

scholarly journals RELATIONSHIP BETWEEN HEDGING RISK MANAGEMENT STRATEGY AND SUPPLY CHAIN PERFORMANCE AMONG MANUFACTURING COMPANIES IN KENYA

2017 ◽  
Vol 1 (2) ◽  
pp. 82-100
Author(s):  
Dr.David Kiarie ◽  
Dr. Patrick Ngugi ◽  
Dr. Kennedy Ogollah
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Sample Size ◽  
Lead Time ◽  
Management Strategy ◽  
Supply Chain Performance ◽  
Manufacturing Companies ◽  
Risk Management Strategy ◽  
Cycle Times ◽  
Supply Chain Costs

Purpose: The purpose of this study was to determine therelationship between hedging risk management strategy and supply chain performance among manufacturing companies in KenyaMethodology:The study adopted a cross-section survey of descriptive nature .The target population comprised of the 412 manufacturing companies within Nairobi County that were registered members of KAM. The fisher et al formula for calculating the sample size was used to yield a sample size of199. Data was collected using questionnaires and analyzed using statistical package of social sciences (SPSS) version 21 as a tool of analysis.Results: The study findings revealed that the companies that increased buffer stock at various levels in the supply chain. Increasing buffer stock at various levels in the supply chain resulted to decreased lead time, improved quality and reduced cost. Results also showed that most of the companies ‘conducted reduce order cycle times. Conducting reduce order cycle times resulted to decreased lead time, improved quality and reduced cost. Further, the results revealed that most of the companies shared supply chain costs with partners. Sharing supply chain costs with partners resulted to decreased lead time, improved quality and reduced cost.Policy recommendation:the study recommended that manufacturing companies should put in place a risk analysis and evaluation management strategy to enhance supply chain performance. In particular, companies should consider conducting whole life costing of suppliers and also internal quality of suppliers.

Supply Chain Performance Management

Controlling ◽  
2003 ◽  
Vol 15 (11) ◽  
pp. 615-622 ◽  
Author(s):  
Carsten Glohr
Keyword(s):  
Supply Chain ◽  
Performance Management ◽  
Supply Chain Performance
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