專案目標、目標承諾與專案績效之探討：大數據分析解決方案

A Study of Project Goal, Goal Commitment and Project Performance: Big Data Analytics Solution

近年企業陸續實施大數據分析解決方案，但大數據專案目前僅有理論、技術層面的相關研究，在大數據專案實施過程中產生的問題鮮少被探討。本研究以目標設定理論探討大數據專案的專案目標設定影響其專案整體績效的因素，以問卷蒐集樣本，基於100份有效問卷發現(1)專案團隊的目標感知困難度對專案整體績效有負面影響，而目標承諾能降低目標感知困難度與專案整體績效間的負向影響；(2)專案團隊的努力能夠弱化專案團隊的目標感知困難度對專案整體績效的負面影響，同時增強目標具體性與專案整體績效間正向的影響，使專案績效更好。本研究結果擴展目標設定理論中，不同情境下專案團隊的目標感知困難度對績效產生負面影響的潛在因素，對理論及實務皆有貢獻。

In recent years, enterprises have successively implemented big data analytics solution projects, but at present, there are only theoretical and technical researches on big data analyze, and problems arising during the process of big data analytics solution implementation have rarely been discussed. This study uses the goal setting theory to explore the factors that affect the overall performance of a big data analytics solution project. Based on 100 valid samples, it is found that (1) the project team’s perceived goal difficulty has a negative impact on the overall project performance, and goal commitment can reduce the negative impact between the perceived goal difficulty and the overall project performance; (2) the efforts of the project team can weaken the negative impact of the perceived goal difficulty on the overall project performance, enhancing the positive impact between goal specification and the overall project performance. The results of this study confirm the potential factors that make perceived goal difficulty negatively affect performance in goal setting theory, and provide possible solutions for companies, contributing to both theory and practice.