零工經濟工作者的生活型態

Abstract

本研究旨在深入剖析零工經濟工作者的生活型態，透過AIO（活動、興趣、意見）生活型態問卷，運用敘述統計分析其基本輪廓，並進一步採用因素分析及集群分析方法，歸納出三大生活型態分群。研究結果顯示，零工經濟工作者的生活型態呈現多元樣貌，且不同分群在人口統計變項（如性別、年齡、婚姻狀況、教育程度、居住區域）及工作狀態變項（如全職/兼職、工作類型、工作年資、工時、收入）上存在顯著差異。具體而言，研究發現可歸納如下：一、三大分群：透過集群分析，將零工經濟工作者區分為「積極參與型」、「經濟導向型」與「消極維持型」三大群體，各群體在工作動機、時間安排、收入期望等方面展現出不同偏好。二、人口統計變項影響：不同性別、年齡、婚姻狀況、教育程度與居住區域的零工經濟工作者，在三大分群的分布上有所差異，顯示人口背景對生活型態的形塑具有一定程度的影響。三、工作狀態變項差異：不同工作型態、工作年資、工時與收入的零工經濟工作者，其生活型態分群亦有所不同，反映工作特性與個人選擇之間的關聯性。本研究不僅描繪出零工經濟工作者的生活型態圖譜，更深入探討了人口統計變項與工作狀態變項對生活型態分群的影響，期能為相關政策制定與實務應用提供參考依據。This study aims to deeply analyze the lifestyle of gig economy workers. It uses narrative statistics to analyze its basic outline through the AIO (Activities, Interests, Opinions) lifestyle questionnaire, and further uses the cluster analysis method to summarize three major lifestyle groups. The research results show that the lifestyles of gig economy workers are diverse, and there are significant differences between different groups in demographic variables (such as gender, age, marital status, education, living area) and working status variables (such as full-time/part-time, job type, working years, working hours, income). Specifically, the research findings can be summarized as follows:1. Three major groups: Through cluster analysis, gig economy workers are divided into three major groups:"active participation", "restricted" and "passive". Each group shows different preferences in terms of work motivation, time arrangement, income expectations, etc. 2. Influence of demographic variables: Gig economy workers with different genders, ages, marital status, education levels and living areas have different distributions among the three major groups, showing that demographic background has a certain degree of influence on the shaping of lifestyles. 3. Differences in working status variables: Gig economy workers with different work types, working years, working hours and income also have different lifestyle groups, reflecting the correlation between work characteristics and personal choices.This study not only depicts the lifestyle map of gig economy workers, but also deeply explores the impact of demographic variables and working status variables on lifestyle grouping. It is expected to provide a reference for relevant policy formulation and practical application.