Survey Data on BEV Adoption of Transport Cooperatives in the Philippines

The dataset titled <em>BEV Adoption Among Transport Cooperatives in the Philippines</em> contains 83 observations and 42 variables collected from medium to large transport cooperatives operating across Luzon, Visayas, and Mindanao. These cooperatives are part of the government’s Public Utility Vehicle Modernization Program (PUVMP) and were selected based on asset classification and franchise eligibility. The primary objective of the dataset is to examine the factors that influence the adoption of Battery Electric Vehicles (BEVs) within the public transport sector.The dataset includes demographic variables that describe the profile of each cooperative. These variables include the geographical area categorized into Area:Luzon (1)Visayas (2), and Mindanao (3), <br>Net worth classification:Up to Php 3,000,000 (1)Php 3,000,001 – 15,000,000 (2) Php 15,000,001 – 100,000,000 (3)More than Php Php100,000,000 (4) <br>Years of operation:Up to 3 years (1)More than 3 to 6 years (2)More than 6 to 9 years (3)More than 9 years (4)<br>, and <br>the percentage of Battery Electric Vehicles (BEVs) in the cooperative's fleet:<br>Between 1% - 25% (2)Between 26% - 50% (3)Between 26% - 50% (4)<br>These serve as important contextual indicators that help frame the cooperative’s capacity and readiness to adopt electric vehicles.<br>The core of the dataset is organized into three thematic blocks: opportunity factors, challenge factors, and BEV adoption indicators. The opportunity factors assess drivers that could encourage the adoption of BEVs. These are divided into three constructs—profit potential, environmental awareness, and technological competitiveness—each measured by several Likert-scaled items. Composite scores for each construct are computed as the mean of their respective indicators. A combined score, labeled “Opportunities,” represents the average perception of the cooperative regarding these enabling factors.Challenge factors, on the other hand, capture perceived barriers to BEV adoption. These are grouped into three constructs as well: startup investment, lack of government support, and infrastructure requirements. Each is again assessed using multiple items on a 4-point Likert scale, with composite scores computed for each construct. The overall “Challenges” score represents the perceived difficulty faced by the cooperative in transitioning to BEVs.<br>The final section of the dataset measures BEV adoption intentions through four indicators that gauge willingness, planning, and commitment to adopt. The responses are again on a 4-point Likert scale, and the average of these items forms the “Adoption” score. This variable acts as the primary outcome variable, allowing the analysis of how perceived opportunities and challenges relate to the cooperatives’ readiness to adopt BEVs.<br>Overall, the dataset offers a structured, multidimensional view of BEV adoption from the lens of Philippine transport cooperatives. With clearly defined constructs and validated measures, it is suitable for regression modeling and comparative analysis. The data suggest that while environmental and technological considerations are strong enablers, financial and infrastructural barriers continue to hinder broader adoption.

本数据集标题为《菲律宾交通合作社的电池电动汽车（Battery Electric Vehicles, BEV）采纳现状》，共包含83条观测样本与42个变量，数据采集自吕宋岛、米沙鄢群岛及棉兰老岛运营的中大型交通合作社。这些合作社隶属于菲律宾政府的公共事业车辆现代化计划（Public Utility Vehicle Modernization Program, PUVMP），筛选依据为资产分类与特许经营资格。本数据集的核心目标是探究影响公共交通领域电池电动汽车（BEV）采纳的各类因素。
数据集包含描述各合作社概况的人口统计学变量，具体包括：地理区域分类：吕宋岛（1）、米沙鄢群岛（2）、棉兰老岛（3）；净资产分级：不超过300万菲律宾比索（1）、3000001至1500万菲律宾比索（2）、15000001至10000万菲律宾比索（3）、超过10000万菲律宾比索（4）；运营年限：不超过3年（1）、3至6年（2）、6至9年（3）、超过9年（4）；以及合作社车队中电池电动汽车（BEV）的占比：1%~25%（2）、26%~50%（3）、26%~50%（4）。上述变量作为重要的情境化指标，可用于刻画合作社采纳电动汽车的能力与准备程度。
数据集的核心内容分为三大主题板块：机遇因素、挑战因素与BEV采纳指标。机遇因素用于评估可推动BEV采纳的驱动因子，划分为三大构面：盈利潜力、环保意识与技术竞争力，每个构面均通过多个李克特（Likert）量表条目进行测量。各构面的综合得分为对应指标的平均值，而总“机遇”得分则代表合作社对上述赋能因素的平均感知水平。
挑战因素则用于捕捉合作社感知到的BEV采纳障碍，同样划分为三大构面：启动投资成本、政府支持缺失与基础设施需求。每个构面同样通过4级李克特量表的多个条目进行评估，并计算各构面的综合得分。总“挑战”得分代表合作社向BEV转型过程中面临的感知难度。
数据集的最后一部分通过四项指标测量BEV采纳意向，涵盖采纳意愿、规划与承诺程度，同样采用4级李克特量表计分，各条目得分的平均值构成“采纳”得分。该变量作为核心因变量，可用于分析感知到的机遇与挑战如何影响合作社的BEV采纳准备度。
总体而言，本数据集从菲律宾交通合作社的视角，提供了关于BEV采纳的结构化多维度视图。其构念定义清晰、测量方式经过验证，适用于回归建模与比较分析。数据表明，尽管环保与技术因素是强有力的赋能因子，但财务与基础设施障碍仍在阻碍BEV的更广泛采纳。