Marlin, Aksioma
Unknown Affiliation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

ANALISIS PENGARUH LONG-TERM RELATIONSHIP, INFORMATION SHARING, TRUST, DAN PROCESS INTEGRATION , TERHADAP KINERJA SUPPLY CHAIN MANAGEMENT (Studi Pada Industri Knalpot di Purbalingga) Marlin, Aksioma; Dwiyanto, Bambang Munas
Diponegoro Journal of Management Volume 6, Nomor 4, Tahun 2017
Publisher : Faculty of Economics and Business Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (135.314 KB)

Abstract

The development of Indonesia's economy cannot be separated from that spread through regions in Indonesia. Purbalingga as one of the districts in Central Java has a potential and growing industrial sector. One of them is the exhaust industry in Pesayangan. The exhaust industry in Purbalingga has huge assets and total production. Like other industries, the exhaust industry in Purbalingga also has problems such as lack of capital funds, product distribution, and supply of raw materials for production. These problems include into supply chain management. Furthermore, the aim this study is to examine the influence of long-term relationship, information sharing, trust, and process integration on supply chain management performance.The population of this study is the company of exhaust industry in Purbalingga which amounts to 148. This research will use a sample of 100 respondents by questionnaires, where the data obtained will be analyzed which covers validity test, reliability test, classical assumption test, multiple regression test, t test, F test and coefficient of determination testThe test results show that the indicators in this study are valid and reliable. The most influential variables are long-term relationship (0,286), then trust (0,208), process integration (0,176), and information sharing (0,169). These results show that all independent variables have a positive and significant influence on the dependent variable supply chain management performance.