The Inventory Leanness and Credit Ratings Dataset: Insights from Pakistan's Manufacturing Sector

Efficient inventory management is pivotal for operational streamlining, waste reduction, and the avoidance of misuse. Inventory mismanagement can severely impact a company's performance, even jeopardizing its credit rating. This study presents the Inventory Leanness and Credit Ratings Dataset, covering data from thirty-eight publicly listed firms on the Pakistan Stock Exchange, all evaluated by PACRA from 2008 to 2018. Data sources include company websites, PACRA reports, and financial statements. Credit ratings were categorized from AAA to C, excluding C and D as they denote impending default. An Empirical Leanness Indicator was devised to gauge inventory efficiency. Control variables like firm size, leverage, capital intensity ratio, and dummy variables for financial losses and subordinate debt were included. This dataset offers researchers the means to test or develop theories regarding the interplay between inventory management and credit ratings in contemporary business operations.高效的库存管理对于业务流程优化、减少浪费以及避免物料滥用至关重要。库存管理失当会严重损害企业经营绩效，甚至危及企业信用评级。本研究发布库存精益性与信用评级数据集（Inventory Leanness and Credit Ratings Dataset），涵盖巴基斯坦证券交易所（Pakistan Stock Exchange）38家上市公司2008至2018年的相关数据，所有样本企业均由PACRA进行信用评级。数据来源包括企业官方网站、PACRA评级报告及企业财务报表。 信用评级等级划分为AAA至C级，剔除C与D级——该两类等级代表企业即将发生违约。本研究设计了实证精益性指标（Empirical Leanness Indicator），用于衡量库存运营效率。数据集纳入了企业规模、财务杠杆率、资本密集度等控制变量，同时包含财务亏损与次级债务的虚拟变量。本数据集可为研究人员提供实证研究手段，以检验或构建当代商业运营场景下库存管理与信用评级之间的交互影响相关理论。