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The aim of the study is to investigate the factors that influence the adoption of e-procurement by businesses in the specific context of Saudi Arabia.

This study uses the firm-level data of World Bank Enterprise Surveys 2022 of Saudi Arabia covering 1,573 enterprises. The association between firm characteristics and the adoption of e-procurement by enterprises has been examined through the chi-square test. Further, a logistic regression model has been fitted to estimate the factors affecting adoption of e-procurement.

About 10 % of the enterprises reported that they adopted e-procurement as the establishment’s main technology to manage procurement and supplier chain by enterprises. A statistically significant association has been found between e-procurement vis-a-vis firm characteristics. Moreover, logistic regression analysis indicated that large and innovative enterprises, with digital presence in terms of website, holding a bank account and access to credit are more likely to adopt e-procurement.

This study offers valuable insights into the factors that influence the adoption of e-procurement by businesses, which helps the supply chain manager to develop and operationalize the digital supply chain through e-procurement in the context of Saudi Arabia.

This paper can provide significant insights for promoters and supply chain managers in Saudi Arabia, who are now focusing on the digital transformation of businesses. By understanding the factors affecting e-procurement by firms, they can smooth the supply chain.

The purpose of the study is to examine the obstacle in doing business and determinants of credit adoption by the textile enterprises in India.

The study is based on World Bank’s Enterprises Survey, there are 571 enterprises involved in textile business. The enterprises survey has response on wide range of business obstacles which are categorized under three broad categories, namely, access to resource, business regulations and market externalities. Chi-square test and analysis of variance (ANOVA) have been used to examine the significant difference among firm’s profile and perceived business obstacles across the firm size. Furthermore, binary logistic regression model has been applied to explore the determinants of credit adoption by textile enterprises.

A statistically significant difference has been found in size of firms and legal status nature of establishment, gender of top manager, main product market and credit adoption from financial institutions. Majority of small- and medium-sized enterprises (SMEs) are sole proprietorship firm while large enterprises are limited partnership firms. Similarly, large enterprises have relatively more female as a top manager and international market for their product. ANOVA reveals equal degree of obstacles in doing textile business across the firm size. The logistic regression coefficient and marginal effects reveal that firm size, main market,gender of owner, number of establishment in the firms positive and significantly affects the credit adoption by 3 textile enterprises.

The study has some policy implications for various stakeholders such as textile business managers and promoters, government, investors and bankers for entrepreneurship development in textile sector. The study suggests that the government should incentivize small- and medium-sized businesses to increase their exports. The results show that despite government efforts to finance SMEs, fewer SMEs are receiving both short- and long-term credit. To help SMEs in the textile industry overcome financial difficulties and expand their main product market to both domestic and international levels, a soft loan should be provided based on the characteristics of textile enterprises.

The present study suggests the evidence-based understanding of textile business environment. The value and uniqueness of this study is to explore an ease of business textile sector using comprehensive enterprises survey data of World Bank.