Artificial intelligence (AI) has emerged as an important strategic tool for improving marketing performance and enhancing the competitiveness of small and medium-sized enterprises (SMEs). Despite its growing adoption, limited empirical evidence explains how different dimensions of organizational readiness influence AI usage in SMEs, particularly in emerging economies. This study investigates the effects of Technological Infrastructure Readiness (TIR), Human Resource Readiness (HRR), and Organizational Culture and Change Management Readiness (OCCMR) on AI Usage Behavior, with Behavioral Intention serving as a mediating variable. The proposed research framework integrates the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), the Technology–Organization–Environment (TOE) framework, the Resource-Based View (RBV), and Organizational Readiness Theory. Data were collected from 402 SME owners and managers in Bangkok, Thailand, and analyzed using covariance-based structural equation modeling (CB-SEM). The measurement model demonstrated satisfactory reliability and validity, while the structural model exhibited an excellent fit (χ²/df = 1.91, CFI = .983, TLI = .978, RMSEA = .047). The results indicate that Technological Infrastructure Readiness, Human Resource Readiness, and Organizational Culture and Change Management Readiness significantly influence Behavioral Intention. In addition, Technological Infrastructure Readiness, Organizational Culture and Change Management Readiness, and Behavioral Intention have significant positive effects on AI Usage Behavior, whereas the direct effect of Human Resource Readiness on AI Usage Behavior is not significant. Behavioral Intention is the strongest predictor of AI Usage Behavior (β = .591, p < .001) and significantly mediates the relationships between organizational readiness and AI adoption.

This paper examines the role of vision as a mediating variable of the relationship between organizational factors and IoT adoption in audit firms in the US. Using a combination of analyses based on structural equation modeling (SEM) and artificial neural network (ANN) technology as the primary research methodology. Seven hypotheses were accepted, including one related to the impact of vision on IoT adoption. In general, all accepted hypotheses had a positive effect on IoT adoption. In addition to the direct positive impact of vision on IoT technology adoption, the magnitude of that effect varied depending on the context of each hypothesis. Drawing evidence from the results, this study demonstrates that vision was a partial mediating variable in the relationship between the organizational factor and IoT adoption. As a result, the model can help audit firms adopt IoT technology successfully. On the other hand, it makes essential recommendations for implementing IoT technology in light of the role that vision plays as a mediating variable in this model. The Technology-Organization-Environment (TOE) framework and Diffusion of Innovation theory (DOI) are combined with the vision to improve model predictive power.

The use of e-procurement aids organisations in reducing business costs, broadening their market access and simplifying purchasing processes. However, in Jordan, only 27.6% of firms utilise e-procurement systems. Hence, the usage of e-procurement systems by Jordanian firms is still in its infancy. In this work, the technology, organisation and environment (TOE) factors affecting the use of e-procurement systems by large firms in Jordan were investigated. Previous studies have reported inconsistent findings with regard to the antecedent factors that may affect e-procurement usage. Therefore, this work aimed to determine the factors related to e-procurement usage and whether or not top management support moderates the relationship between TOE factors and e-procurement usage. Results revealed that all TOE factors used in this study influenced the e-procurement usage of the firms. Moreover, the moderating role of top management support was found to be positively related to relative advantages and organisational readiness and negatively related to complexity.

The study challenges the previous literature and assumes the digital vision as a proxy of intention among Technological, Organizational, and Environmental (TOE) factors and investigates the influence of TOE factors on cloud accounting adoption among Small and Medium Enterprises (SMEs). Furthermore, the effect of cloud accounting adoption on the organization's performance as measured by the balanced scorecard was evaluated. The data collection strategy employed an online survey of owners and managers using snowball methodology, in which the survey was automatically introduced to the respondents most likely to find relevant. The data was validated prior to SEM analysis. Seven of eight hypotheses were accepted, including the two hypotheses about the impact of the digital vision on cloud accounting adoption and the hypothesis about the impact of cloud accounting adoption on balanced scorecard-measures organizational performance. Despite the importance of the statistically significant factors in the study model, the digital vision was the most affected by the organizational readiness factor. The findings contribute to the TOE model by challenging the previous literature and assumption of digital vision as a proxy of intention among TOE factors. Future studies should use the TOE framework more caution if the intention is assumed to be a mediating variable.