Multi-Pillar Construction Supervision and Sustainability Performance Dataset (PLS-SEM)

Research Hypothesis The core hypothesis of this study posits that Sustainable Construction Supervision Performance (SCSP) on building sites in rapidly urbanizing regions is heavily constrained by systemic structural bottlenecks, specifically Professional Capacity Deficiencies (PCD) and Regulatory Ambiguity (RA). Conversely, it is hypothesized that proactive Professional Competence of Supervisors and structured Stakeholder Collaboration act as vital enabling mechanisms that can directly counter these barriers and significantly improve multi-pillar sustainability compliance (Environmental, Economic, Social, and Technological) in the field. What the Data Shows & How It Was Gathered sustainable_construction_supervision_raw_data.xlsx consists of empirical field metrics captured across 150 active building construction sites in Sylhet, Bangladesh. A multi-informant survey design was utilized to collect data from 597 active field practitioners, including Site Engineers, Project Managers, Contractors, and Construction Supervisors. This structural matrix features 50 distinct variables, yielding 29,850 discrete data entries with zero missing values. The dataset evaluates performance using two primary measurement structures: 5-Point Likert Scales (1 = Strongly Disagree to 5 = Strongly Agree): Used to quantify subjective operational realities, including the four pillars of sustainability (Environmental, Economic, Social, Technological), (see "Questionnaire.docx"). Binary Indicators (1 = Yes, 0 = No): Deployed to map explicit on-site technical capacities and actual digital tool utilization rates. Notable Findings The Technological Deficit: The data exposes a severe gap in digital workflows. Building Information Modeling (BIM) adoption scored an industry-wide low (Mean = 1.84, SD = 0.88). Furthermore, binary tracking reveals that while mobile site communication is widespread (71%), advanced practices like cloud-based reporting (28%) and automated safety monitoring (14%) remain largely unadopted. Primary Systemic Bottlenecks: Practitioners pointed to a Lack of Qualified Professionals (Mean = 4.18, SD = 0.63) and Ambiguous Regulatory Frameworks (Mean = 4.09, SD = 0.66) as the most critical structural constraints halting sustainable transition. Acute Skills Gaps: Binary diagnostic items show that 72% of active site supervisors completely lack formal sustainability training, 64% operate with insufficient environmental compliance knowledge, and 78% have zero technical proficiency in digital engineering tools. The Core Enablers: The Professional Competence of Supervisors (Mean = 4.42, SD = 0.54) and Collaboration Among Stakeholders (Mean = 4.26, SD = 0.61) emerged with the highest baseline agreement as the most powerful drivers for project success. Data Interpretation and Use Researchers can model the direct path coefficients β & inner relationships between organizational barriers & sustainability outcomes by mapping these 50 indicators.研究假设 本研究的核心假设指出：快速城市化地区施工现场的可持续施工监理绩效（Sustainable Construction Supervision Performance, SCSP）深受系统性结构瓶颈的制约，具体表现为专业能力不足（Professional Capacity Deficiencies, PCD）与监管模糊性（Regulatory Ambiguity, RA）。反之，本研究同时假设：主动提升的监理人员专业能力与规范化的利益相关方协作，可作为关键赋能机制，直接抵消上述障碍，并显著提升施工现场多维度可持续合规性——涵盖环境、经济、社会与技术四大维度。 数据内容与采集方式 本数据集sustainable_construction_supervision_raw_data.xlsx包含孟加拉国锡尔赫特市150个在建建筑施工现场采集的实地实证指标。研究采用多信息提供者调研设计，从597名一线现场从业人员（含现场工程师、项目经理、承包商与施工监理）处收集数据。该结构化数据集共包含50个独立变量，生成29850条离散数据条目，无缺失值。 本数据集采用两类核心测量结构对绩效进行评估： 1. 李克特五点量表（1=完全不同意至5=完全同意）：用于量化主观运营现状，涵盖可持续性四大维度（环境、经济、社会、技术），详见"Questionnaire.docx"。 2. 二元指标（1=是，0=否）：用于映射施工现场明确的技术能力与实际数字工具使用率。 关键研究发现 技术短板：数据揭示了数字工作流存在严重缺口。建筑信息模型（Building Information Modeling, BIM）的行业整体采用率极低（均值=1.84，标准差=0.88）。此外，二元指标追踪显示，尽管移动端现场沟通的普及率达71%，但基于云的报告、自动化安全监控等先进实践的采用率仅分别为28%与14%，整体普及度仍极低。 核心系统性瓶颈：受访从业人员指出，合格专业人员短缺（均值=4.18，标准差=0.63）与监管框架模糊（均值=4.09，标准差=0.66）是阻碍可持续转型的最关键结构性约束。 严重技能缺口：二元诊断条目数据显示，72%的在岗现场监理人员完全未接受过正规可持续性培训，64%的人员缺乏足够的环境合规知识，78%的人员完全不具备数字工程工具的技术操作能力。 核心赋能机制：监理人员专业能力（均值=4.42，标准差=0.54）与利益相关方协作（均值=4.26，标准差=0.61）的基线认可度最高，被视为推动项目成功的最有力驱动因素。 数据解读与应用 研究人员可通过映射这50个指标，构建组织障碍与可持续性结果之间的直接路径系数β及内部关联模型。