Digital business transformation is considered an effective business strategy that appears to have gained attention since the enterprises are challenged to continuously improve their business practices as well as capabilities. The use of digital technologies could reduce the influence of external crises and could introduce massive changes in business operations by providing better business models. Moreover, adopting digital technology can influence both economic sustainability and social value of enterprises and can improve regional socio-economic conditions. There are few recent studies on how technology can empower enterprises at different phases of growth and sustainability; furthermore, very few studies are available that determine how adopting different modern digital technologies can create value for small and medium enterprises (SMEs). Therefore, this study aims to close this gap and investigate the moderating role of entrepreneurial orientation. With the support of resource-based view (RBV) and dynamic capability view (DCV) theories, along with a literature review, a theoretical model has been developed. It was then validated using the PLS-SEM technique considering 319 respondents who are SME employees in India. The findings show that adopting digital technologies has a significant impact on the creation of economic sustainability and social value for SMEs. The study also found a significant moderating impact of entrepreneurial orientation on the relationship between social and economic value creation and SME performance.

Purpose: The purpose of this study is to identify the determinants that could impact corporate digital entrepreneurship for the small and medium enterprises (SMEs) of India. The study also investigates the moderating role that adopting artificial intelligence (AI)-customer relationship management (CRM) capability and strategic planning has in corporate digital entrepreneurship.Design/methodology/approach: With the inputs from literature and theories, a model has been developed conceptually. The model has been validated by partial least squares structural equation modeling technique with consideration of 315 usable respondents. The effects of the moderators have also been investigated by multigroup analysis.Findings: The study highlights that perceived usefulness, perceived ease of use and willingness to change significantly impact corporate digital entrepreneurship for the SMEs of India. The study also highlights that the two moderators have significant impacts on the relationships between corporate digital entrepreneurship and its predictors.Research limitations/implications: This study has developed a unique model, which provides effective inputs to the entrepreneurs of SMEs of emerging economies. These inputs will help entrepreneurs to frame their policies to improve the existing traditional practices and processes that could be transformed into more digitalization for improving efficiency of their corporate digital entrepreneurial activities.Originality/value: There are no studies which investigated how perceived usefulness, perceived ease of use and willingness to change could impact corporate digital entrepreneurship with the moderating effects of adoption of AI-CRM capability and strategic planning, as concerns SMEs of emerging economies. In this regard, this study is deemed to be a unique attempt.

Purpose: The purpose of this paper is to develop a conceptual framework to check if an organization is ready to adopt an AI-integrated CRM system. The study also analyzes different situations which can provide a comprehensive check list in the form of indicators that could provide a signal indicating whether the organization is ready to adopt an AI-integrated CRM system by capturing actionable and appropriate data. Design/methodology/approach: The paper is a general review, and appropriate literature has been used to support the conceptual framework. Findings: The key findings of this study are the different indicators that make up the conceptual framework. This framework can help organizations to check at a glance whether they are ready to adopt AI-integrated CRM system in their organizations. Specifically, it has been identified that different approaches are needed to tackle various types of customer data so that those may be made fit and actionable for appropriate utilization of AI algorithms to facilitate business success of an organization. Practical implications: The paper has elaborately discussed the different approaches to be undertaken to calibrate and reorient the various kinds of actionable data and the contemplated challenges one would face in doing so. This would help the practitioners that how the data so captured can be made fit for action and utilization toward application of AI technologies integrated with existing CRM system in an organization. Originality/value: This study is claimed to be a unique study to provide a conceptual framework which could help arranging and rearranging of captured data by an organization for making the data fit and ready for use with the help of AI technologies. This successful integration of AI with CRM system can help organizations toward taking quick and automated decision-making without much intervention of human beings.