International Journal of Information Systems and Change Management (5 papers in press)

Regular Issues

• Unravelling E-Governance Adoption Drivers: Insights from the UTAUT 3 Model  
  by Saurabh Gupta, Sadananda Prusty, Medha Srivastava 
  Abstract: The study aims to unveil the various determinants that drive the adoption of E-governance services (EGS). Using the UTAUT 3 model, the research investigated these factors within the Indian context. A purposive sampling technique was utilised to collect the samples from 680 respondents through the online survey method. Furthermore, the study employs structural equation modelling (SEM) to examine the structural relationships between UTAUT3 models dimensions in the context of e-governance. Findings revealed that the UTAUT3 model adequately predicts the intention to adopt EGS. The present study addressed a significant gap in the literature on EGS and technology adoption by establishing a relationship between different dimensions of the UTAUT3 model and actual usage of EGS. The findings have implications for practitioners and policymakers as it throws light on the effective implementation of e-governance programs which are essential for providing the citizens with high-quality services.
  Keywords: E-governance; Government services; UTAUT3; Personal Innovativeness; Common Service Centres; Structural Equation Modelling.
  DOI: 10.1504/IJISCM.2024.10066080
   
  
• Predicting Green Entrepreneurial Intention among Farmers using Theory of Entrepreneurial Event and Institutional Theory  
  by Geetha Krishnan, J.N.V. Raghuram 
  Abstract: Green Entrepreneurial Intention (GEI) in the agriculture sector signifies agricultural businesses' strong determination to embrace environmentally sustainable practices and innovative eco-friendly approaches. To understand farmers' Green Entrepreneurial Intention, the research applied theory of entrepreneurial event and institutional theory. A model was developed and empirically validated through Structural Equation modelling. A questionnaire survey was used to collect data from 211 farmers from the southern region of India. Findings revealed that Perceived Desirability, Perceived Feasibility, Mimetic Pressure, and Entrepreneurial Mindset positively influenced GEI. Entrepreneurial Mindset played a mediating role in strengthening the farmers Green entrepreneurial intention. This study contributes to understanding GEI in agriculture and informs strategies for promoting sustainable farming practices.
  Keywords: Perceived Desirability; Perceived Feasibility; Mimetic Pressure; Entrepreneurial Mindset; Green Entrepreneurial Intention; Theory of entrepreneurial event; Institutional theory.
  DOI: 10.1504/IJISCM.2024.10066209
   
  
• Assessing Supply Chain Risk Management Capabilities and its Impact on Supply Chain Performance: Moderation of AI-embedded Technologies  
  by Xiangli Meng, Na An 
  Abstract: Effective risk management in the supply chain is crucial to ensure resilience and continuity. It safeguards against disruptions, minimizes financial losses, and enhances overall performance. However, Artificial intelligence (AI) integration in supply chain management enhances efficiency by automating processes, predicting demand, and optimizing logistics. Current research investigates the correlation between risk management and supply chain performance along with moderation of AI-embedded technologies such as big data analytics, IoT, virtual reality, and blockchain technologies. To calculate the results, this study utilized six hundred and forty-four questionnaires through structural equation modeling method. It is revealed using SmartPls that financial risk management (FRM) is positively linked with supply chain performance (SCP). Second, it was observed that AI significantly moderates the connection between FRM and SCP. In addition, the study presents certain insights into supply chain and AI-enabled technologies that how these capabilities can beneficially advance SCP. Besides, certain implications both managerial and theoretical are described for the supply chain managers along with limitations for future scholars of the world.
  Keywords: Supply chain management; risk management; financial risk; AI-enabled technologies; structural equation modeling.
  DOI: 10.1504/IJISCM.2024.10066269
   
  
• Entrepreneurship vs. Mentorship: An Analysis of Leaderships Modes on Sustainable Development with Moderation of Innovation Management  
  by Liping Wang  
  Abstract: This study explores the connection between mentorship and sustainable development (SD) within three major perspective of sustainable development such as social, environmental, and economic perspective from China. Second, the study revealed the relationship between entrepreneurship and SD. Third, a moderation influence of innovation management (IM) was observed among the proposed nexuses of mentorship, entrepreneurship, and SD. To this end, a total of 535 questionnaires were eventually utilised with the support of SmartPLS and structure equation modelling (SEM) approach. A positive connection was confirmed between mentorship and SD. The outcome uncovered a positive correlation between entrepreneurship and SD. In addition, a moderation of IM was found between mentorship, entrepreneurship, and SD. The study enlists several interesting lines about mentorship, entrepreneurship, and IM that might helpful improving SD in terms of social, environmental, and economic perspectives. Besides, the study provides various implications for management and states the weaknesses along with the future directions for worldly researchers.
  Keywords: mentorship; entrepreneurship; sustainable development; innovation management; structure equation modeling.
  DOI: 10.1504/IJISCM.2024.10066398
   
  
• Investigation of User Perception of Software Features for Software Architecture Recovery in Object Oriented Software  
  by Neeraj Kumar, Randeep Singh, Amit Rathee 
  Abstract: A well-documented architecture can greatly improve comprehension and maintainability. However, shorter release cycles and quick deliveries pattern results in negligence of architecture. In such situations, the architecture can be recovered from its current implementation based on considering dependency relations. In literature, structural and semantic dependencies are commonly used software features, and directory information along with co-change/change history information are among rarely utilised software features. But, they are found to help improve architecture recovery. Therefore, we consider investigating various features that may further improve the accuracy of existing architecture recovery techniques and evaluate their feasibility by considering them in different pairs. We compared five state-of-the-art methods under different feature subsets. We identified that two of them commonly outperform others but surprisingly with low accuracy in some evaluations. Further, we propose a new subset of features that reflects more accurate user perceptions and hence, results in improving the accuracy of architecture recovery techniques.
  Keywords: Software Architecture; Architecture Recovery; Software Features; Empirical Evaluation; User Perception.
  DOI: 10.1504/IJISCM.2024.10066399