TY - JOUR
T1 - The Effectiveness of Measuring in Supply Chain Operations of E-Marketers
AU - Nguyen, Phu An
AU - Sanyal, Shouvik
AU - Nguyen, Hat Dang
AU - Bohidar, Chapala
AU - Okeke, Augustine
AU - Narawish, Chutimon
PY - 2022/1/20
Y1 - 2022/1/20
N2 - Supply Chain Management (SCM) for automotive manufacturers worldwide is one of the most relevant and dynamic problems. This research aims to analyse factors affecting the strategic efficiency of the supply chain (SPSC) and the OPSC by quantitative and quality research in the automotive industries. The research aims to evaluate the main outcomes, such as checked theories and established levels of buildings between IKCO and Isuzu, as studies in the automotive industry. In total, IKCO and Isuzu businesses received a total of 217 and 201 completed questionnaires. SPSS analyses Cronbach's Alpha, where all values of Alpha are highly reasonable, also tested the reliability of results. Path analyses (PA) were engaged in discovering the occasional relationship between variables through multi-regression in PHSA, according to SPSC and OPSC as the key-dependent variables. SPSC and OPSC have been structured, based on the PA methodology, to assess IKCO and Isuzu's distribution chain efficiency. The Maximal Factor Likelihood (ML), used for the study of normality, outliers and composite stability, validity, and evaluating theories of Amos, was the foundation for confirmatory factor analyses (CFA). The qualitative analysis was also conducted to clarify the dimensions and assess the actual condition through interviews and documents. In conclusion, study results show that IT, organizational learning (OL), and product creativity (PRI) have affected the strategic success of the supply chain. However, SPSC has little impact on transformational leadership. In addition, method innovation (PI) and relationship efficiency affected the organizational output of the supply chain (PQ). The SPSC and OPSC have first been studied in the automobile sector. The research difference has been established, and the research center and SCM as the key foundation for automotive producers have been recognized.
AB - Supply Chain Management (SCM) for automotive manufacturers worldwide is one of the most relevant and dynamic problems. This research aims to analyse factors affecting the strategic efficiency of the supply chain (SPSC) and the OPSC by quantitative and quality research in the automotive industries. The research aims to evaluate the main outcomes, such as checked theories and established levels of buildings between IKCO and Isuzu, as studies in the automotive industry. In total, IKCO and Isuzu businesses received a total of 217 and 201 completed questionnaires. SPSS analyses Cronbach's Alpha, where all values of Alpha are highly reasonable, also tested the reliability of results. Path analyses (PA) were engaged in discovering the occasional relationship between variables through multi-regression in PHSA, according to SPSC and OPSC as the key-dependent variables. SPSC and OPSC have been structured, based on the PA methodology, to assess IKCO and Isuzu's distribution chain efficiency. The Maximal Factor Likelihood (ML), used for the study of normality, outliers and composite stability, validity, and evaluating theories of Amos, was the foundation for confirmatory factor analyses (CFA). The qualitative analysis was also conducted to clarify the dimensions and assess the actual condition through interviews and documents. In conclusion, study results show that IT, organizational learning (OL), and product creativity (PRI) have affected the strategic success of the supply chain. However, SPSC has little impact on transformational leadership. In addition, method innovation (PI) and relationship efficiency affected the organizational output of the supply chain (PQ). The SPSC and OPSC have first been studied in the automobile sector. The research difference has been established, and the research center and SCM as the key foundation for automotive producers have been recognized.
UR - https://www.mendeley.com/catalogue/a30f55ca-6c98-3d1d-af38-83d535a83aa2/
U2 - 10.14704/WEB/V19I1/WEB19153
DO - 10.14704/WEB/V19I1/WEB19153
M3 - Article
SN - 1735-188X
VL - 19
SP - 2245
EP - 2264
JO - Webology
JF - Webology
IS - 1
ER -