The impact of access to credit on process innovation

Abstract

<jats:p>The effectiveness of a firm mostly depends on the capability of the managers to obtain flexible credits for the implementation of sustainable innovations. The aim of this study is focused on the impact of access to credit on process innovations in SMEs. Data from the manufacturing and the service sectors of the economies of Africa and the Middle East are collected from the World Bank’s Enterprise Survey database. The survey employs random sampling to select firms in each country and they are stratified based on the number of employees. The sampled observations are scaled down from 136,887 to 33,977 firms covering 53 countries due to the scope of this research. The factors of access to credit are the independent variables of this research: the working capital from a commercial bank, overdraft facility, lines of credit, external auditing of accounts, and working capital from suppliers. The dependent variable is process innovation. The results show that there are significance levels of p-values below 1% although some of the Pearson correlation coefficients of the independent variables with the dependent variable are not too high. The factors of access to credit used in the regression model have a significant impact on process innovation. The findings from the analysis help the policy directions of managers.</jats:p>

Dynamic Mathematical Models’ System and Synchronization

“…e HYCH system with a multidimensional space is more effective and precompiled than the low dimension, and it surpasses typical 3D, 4D, and 5D systems due to its enhanced unpredictability and randomness. ere have been an increasing number of articles on the development of new high-dimensional (9D) [16][17][18][19][20] systems with four basic components LYP exponents, as well as several papers on the development of new strong (6D) [21][22][23][24][25] systems with four test LYP coefficients. In [26][27][28][29][30], a six-dimensional HYCH system with four positive LYP exponents is constructed: LEA 1 � 0.5311, LEA 1 � 0.3100, LEA 3 � 0.1300, LEA 4 � 0.0780, LEA 5 � -0.0001, and LEA 5 � -12.5224, consisting of 14 terms; three terms are described.…”

Appliance to Predict the Quality of Hypothetically Modified Products

“… B2B -business-to-business [21],  B2C -business to customer [22],  Brainstorming (BM) [5],  CI -comparison matrix (CI) [10],  CR -concordance ratio [6],  medium-sized companies (SMEs) [23],  QFD -Quality Function Deployment [11,12],  S = (S ij ) -square matrix (dominance) [6],  SMARTER (Specific, Measurable, Achievable, Relevant, Time-Based, Exciting, Recorded) [30],  W i w -weights of criteria [10,6],  WSM -Weighted Sum Model [27,28].…”

“…The analysis was based on, e.g., impact B2B onto actions of these companies. In turn, the authors of the work [23] have focused on the impact of access to credit on process innovation in SMEs. The results have applications to help the managers' policy directions.…”

Banks Credit Risk Prediction with Optimized ANN Based on Improved Owl Search Algorithm

“…e most significant factor in economic development in every country is the correct relationship between financial and production systems [1]. Banks will play an essential role in supplying manufacturing, commercial, consumable, and even government sectors as the central part of the financial system.…”