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This paper presents a qualitative study of penetration testing, the practice of attacking information systems to find security vulnerabilities and fixing them. The purpose of this paper is to understand whether and to what extent penetration testing can reveal various socio-organisational factors of information security in organisations. In doing so, the paper innovates theory by using Routine Activity Theory together with phenomenology of information systems concepts.

The articulation of Routine Activity Theory and phenomenology emerged inductively from the data analysis. The data consists of 24 qualitative interviews conducted with penetration testers, analysed with thematic analysis.

The starting assumption is that penetration testers are akin to offenders in a crime situation, dealing with targets and the absence of capable guardians. A key finding is that penetration testers described their targets as an installed base, highlighting how vulnerabilities, which make a target suitable, often emerge from properties of the existing built digital environments. This includes systems that are forgotten or lack ongoing maintenance. Moreover, penetration testers highlighted that although the testing is often predicated on planned methodologies, often they resort to serendipitous practices such as improvisation.

This paper contributes to theory, showing how Routine Activity Theory and phenomenological concepts can work together in the study of socio-organisational factors of information security. This contribution stems from considering that much research on information security focuses on the internal actions of organisations. The study of penetration testing as a proxy of real attacks allows novel insights into socio-organisational factors of information security in organisations.

With the growing concern of various sectors of society regarding environmental issues and the promotion of sustainable development, green technology innovation is generally considered to be conducive to the long-term development of enterprises. However, because of the existence of agency problems, managers may have shortsighted behaviors. Then how will managers' shortsighted behaviors affect enterprises' green technology innovation?

This paper uses machine learning-based text analysis methods to construct a manager myopia index based on the data from A-share listed companies on the Shanghai and Shenzhen Stock Exchanges from 2015 to 2020. We examine the impact of manager myopia on green technology innovation in companies.

Our study finds that manager myopia significantly inhibits green technology innovation in companies. However, when multiple large shareholders coexist and the proportion of institutional investors' holdings is high, it can alleviate the inhibitory effect of manager myopia on green innovation. Heterogeneity tests show that the impact of manager myopia on green technology innovation is relatively significant in non-state-owned and manufacturing companies, as well as in the electricity industry. Robustness tests demonstrate that our conclusions remain valid after using propensity score matching to eliminate endogeneity problems.

From the perspective of corporate governance, this paper incorporates managers' shortsightedness, multiple large shareholders and institutional investors' shareholding ratios into the same logical framework, analyzes their internal mechanisms, helps improve corporate governance, enhances green innovation capabilities and has strong implications for the implementation of national innovation-driven development strategies and the achievement of “carbon peak” and “carbon neutrality” targets.

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.