Business Process Reengineering (Normalized)

This dataset provides processed and normalized/standardized indices for the management tool 'Business Process Reengineering' (BPR). Derived from five distinct raw data sources, these indices are specifically designed for comparative longitudinal analysis, enabling the examination of trends and relationships across different empirical domains (web search, literature, academic publishing, and executive adoption). The data presented here represent transformed versions of the original source data, aimed at achieving metric comparability. Users requiring the unprocessed source data should consult the corresponding BPR dataset in the Management Tool Source Data (Raw Extracts) Dataverse. Data Files and Processing Methodologies: Google Trends File (Prefix: GT_): Normalized Relative Search Interest (RSI) Input Data: Native monthly RSI values from Google Trends (Jan 2004 - Jan 2025) for the query \"business process reengineering\" + \"process reengineering\" + \"reengineering management\". Processing: None. The dataset utilizes the original Google Trends index, which is base-100 normalized against the peak search interest for the specified terms and period. Output Metric: Monthly Normalized RSI (Base 100). Frequency: Monthly. Google Books Ngram Viewer File (Prefix: GB_): Normalized Relative Frequency Input Data: Annual relative frequency values from Google Books Ngram Viewer (1950-2022, English corpus, no smoothing) for the query Reengineering + Business Process Reengineering + Process Reengineering. Processing: The annual relative frequency series was normalized by setting the year with the maximum value to 100 and scaling all other values (years) proportionally. Output Metric: Annual Normalized Relative Frequency Index (Base 100). Frequency: Annual. Crossref.org File (Prefix: CR_): Normalized Relative Publication Share Index Input Data: Absolute monthly publication counts matching BPR-related keywords [(\"business process reengineering\" OR ...) AND (\"management\" OR ...) - see raw data for full query] in titles/abstracts (1950-2025), alongside total monthly publication counts in Crossref. Data deduplicated via DOIs. Processing: For each month, the relative share of BPR-related publications (BPR Count / Total Crossref Count for that month) was calculated. This monthly relative share series was then normalized by setting the month with the maximum relative share to 100 and scaling all other months proportionally. Output Metric: Monthly Normalized Relative Publication Share Index (Base 100). Frequency: Monthly. Bain & Co. Survey - Usability File (Prefix: BU_): Normalized Usability Index Input Data: Original usability percentages (%) from Bain surveys for specific years: Reengineering (1993, 1996, 2000, 2002); Business Process Reengineering (2004, 2006, 2008, 2010, 2012, 2014, 2017, 2022). Processing: Semantic Grouping: Data points for \"Reengineering\" and \"Business Process Reengineering\" were treated as a single conceptual series for BPR. Normalization: The combined series of original usability percentages was normalized relative to its own highest observed historical value across all included years (Max % = 100). Output Metric: Biennial Estimated Normalized Usability Index (Base 100 relative to historical peak). Frequency: Biennial (Approx.). Bain & Co. Survey - Satisfaction File (Prefix: BS_): Standardized Satisfaction Index Input Data: Original average satisfaction scores (1-5 scale) from Bain surveys for specific years: Reengineering (1993, 1996, 2000, 2002); Business Process Reengineering (2004, 2006, 2008, 2010, 2012, 2014, 2017, 2022). Processing: Semantic Grouping: Data points for \"Reengineering\" and \"Business Process Reengineering\" were treated as a single conceptual series for BPR. Standardization (Z-scores): Original scores (X) were standardized using Z = (X - ?) / ?, with a theoretically defined neutral mean ?=3.0 and an estimated pooled population standard deviation ??0.891609 (calculated across all tools/years relative to ?=3.0). Index Scale Transformation: Z-scores were transformed to an intuitive index via: Index = 50 + (Z * 22). This scale centers theoretical neutrality (original score: 3.0) at 50 and maps the approximate range [1, 5] to [?1, ?100]. Output Metric: Biennial Standardized Satisfaction Index (Center=50, Range?[1,100]). Frequency: Biennial (Approx.). File Naming Convention: Files generally follow the pattern: PREFIX_Tool_Processed.csv or similar, where the PREFIX indicates the data source (GT_, GB_, CR_, BU_, BS_). Consult the parent Dataverse description (Management Tool Comparative Indices) for general context and the methodological disclaimer. For original extraction details (specific keywords, URLs, etc.), refer to the corresponding BPR dataset in the Raw Extracts Dataverse. Comprehensive project documentation provides full details on all processing steps.

本数据集为管理工具业务流程再造（Business Process Reengineering, BPR）提供经过处理与归一化/标准化的指标。该数据集源自5个独立的原始数据源，专为纵向比较分析设计，可用于考察不同实证研究领域（网络搜索、文献研究、学术出版与高管采纳情况）内的趋势与关联关系。本数据集呈现的是原始源数据经过转换后的版本，旨在实现指标的可比性。若用户需要未经过处理的原始源数据，请参阅《管理工具源数据（原始提取数据）》Dataverse数据集中对应的BPR数据集。

数据文件与处理方法：
Google Trends文件（前缀：GT_）：归一化相对搜索热度（RSI）
输入数据：来自Google Trends的原生月度相对搜索热度（RSI）值（2004年1月至2025年1月），对应查询词为"business process reengineering"、"process reengineering"与"reengineering management"。
处理方式：未进行额外处理。本数据集采用原生Google Trends指数，该指数以指定查询词与时间段内的搜索热度峰值为基准，以100为基准进行归一化。
输出指标：月度归一化相对搜索热度（基准值100）。
更新频率：月度。

Google Books Ngram Viewer文件（前缀：GB_）：归一化相对频率指数
输入数据：来自Google Books Ngram Viewer的年度相对频率值（1950年至2022年，英语语料库，未进行平滑处理），对应查询词为Reengineering、Business Process Reengineering与Process Reengineering。
处理方式：将年度相对频率序列中数值最大的年份设为100，其余年份按比例缩放，完成归一化。
输出指标：年度归一化相对频率指数（基准值100）。
更新频率：年度。

Crossref.org文件（前缀：CR_）：归一化相对出版物占比指数
输入数据：1950年至2025年间，标题/摘要中包含BPR相关关键词（["business process reengineering" OR ...] AND ["management" OR ...]，完整查询词详见原始数据）的月度绝对出版物数量，以及Crossref平台的月度总出版物数量。通过DOI进行数据去重。
处理方式：每月计算BPR相关出版物的相对占比（BPR数量 / 当月Crossref总出版物数量），随后将该月度相对占比序列中数值最大的月份设为100，其余月份按比例缩放，完成归一化。
输出指标：月度归一化相对出版物占比指数（基准值100）。
更新频率：月度。

Bain & Co.调研——易用性文件（前缀：BU_）：归一化易用性指数
输入数据：贝恩咨询针对特定年份的原始易用性百分比数据：Reengineering（1993、1996、2000、2002年）；Business Process Reengineering（2004、2006、2008、2010、2012、2014、2017、2022年）。
处理方式：语义分组：将"Reengineering"与"Business Process Reengineering"的数据点合并为BPR的单一概念序列。归一化：将合并后的原始易用性百分比序列以其自身所有纳入年份中的历史最高值为基准，归一至100。
输出指标：双年度估算归一化易用性指数（以历史峰值为基准，基准值100）。
更新频率：双年度（近似）。

Bain & Co.调研——满意度文件（前缀：BS_）：标准化满意度指数
输入数据：贝恩咨询针对特定年份的原始平均满意度评分（1-5分量表）：Reengineering（1993、1996、2000、2002年）；Business Process Reengineering（2004、2006、2008、2010、2012、2014、2017、2022年）。
处理方式：语义分组：将"Reengineering"与"Business Process Reengineering"的数据点合并为BPR的单一概念序列。标准化（Z分数）：原始评分(X)通过公式Z=(X - μ)/σ进行标准化，其中理论中性均值μ=3.0，估算的合并总体标准差σ≈0.891609（基于所有工具/年份相对于μ=3.0的数据计算得出）。指标量表转换：将Z分数转换为直观指数，公式为：Index = 50 + (Z * 22)。该量表将理论中性值（原始评分3.0）居中至50，并将近似区间[1, 5]映射至[-1, 100]。
输出指标：双年度标准化满意度指数（中心值=50，区间约[1, 100]）。
更新频率：双年度（近似）。

文件命名规范：文件通常遵循`PREFIX_Tool_Processed.csv`或类似格式，其中`PREFIX`代表数据源（GT_、GB_、CR_、BU_、BS_）。如需了解整体背景与方法学免责声明，请参阅父数据集"管理工具比较指数"的描述。如需获取原始提取细节（具体关键词、URL等），请参阅《原始提取数据》Dataverse数据集中对应的BPR数据集。完整的项目文档提供了所有处理步骤的详细说明。