Demographic determinants of electronic commerce (EC) adoption by SMEs

The determinants of smart government systems adoption by public sector organizations in Saudi Arabia

This study investigates the determinants of smart government systems that are used in public service organizations in Saudi Arabia. The world's developed nations have conducted studies on smart government systems, but little research has been done on the Middle East, particularly in Saudi Arabia. This study fills the lacuna in the literature. Based on a number of theories including the Technology, Organization, and Environment framework (TOE), Unified Theory of Acceptance and Use of Technology (UTAUT), and Technology Acceptance Models (TAM), the study established an integrated conceptual research model. Online survey questionnaires were sent to 2060 employees in four ministries and after the second reminder a total of 427 completed answers were received, of which 419 (22% response rate) were deemed useable for the analysis. Multivariate statistical analysis was used to analyze the data and results indicated that 51% of the variance (R2 = 0.51) of employees' perceptions of smart government systems is explained by independent determinants. Findings show that security concerns (t (419) = 2.051, p < 0.041), ICT strategy (t (419) = 4.215, p < 0.000), managerial support (t (419) = 5.027, p < 0.000), incentives (t (419) = 5.263, p < 0.000), and trust (t (419) = -1.957, p < 0.050) are significant predictors of smart government systems acceptance. Meanwhile cultural values (t (419) = 0.669, p < 0.504) and religious values (t (419) = 1.082, p < 0.280) have no significant effect on the attitude to smart system adoption. Perception was found to have a strong significant effect on adoption of smart government systems (t (419) = 8.411, p < 0.000). These results have significant implications for the Saudi government's drive to implement smart government systems in all its agencies.

Extending the UTAUT model to understand the barriers towards SME digitalization

Digitalization has been identified as a core growth driver for small and medium enterprises (SMEs) in this digital era. This study investigates the drivers and barriers aligned with the tendency of owner-managers of SMEs to adopt digitalization. A conceptual framework is developed that extends the unified theory of acceptance and technology (UTAUT) with an anxiety-digitalized environment as a moderating factor of SME owner-managers' intention to adopt digitalization. A quantitative methodology is used to gauge responses from 89 respondents (owner-managers). Additionally, the variance-based structural equation modelling approach (PLS-SEM) is used to analyse and validate the proposed model. Results show that attitude positively mediates the relationship between performance expectancy and intention to adopt digitalization. However, effort expectancy and facilitating conditions were found to negatively influence attitude and intention to adopt digitalization. On the contrary, the results obtained did not confirm the significance of an anxiety-digitalized environment in moderation analyses. Consequently, the overall structural model accounted for 51.1% of the variance in the intention to adopt digitalization among SMEs. This study has theoretically and practically contributed to understanding owner-managers' intent to adopt digitalization of SMEs in the Czech Republic.

Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations

Purpose

Human resource managers are adopting AI technology for conducting various tasks of human resource management, starting from manpower planning till employee exit. AI technology is prominently used for talent acquisition in organizations. This research investigates the adoption of AI technology for talent acquisition.

Design/methodology/approach

This study employs Technology-Organization-Environment (TOE) and Task-Technology-Fit (TTF) framework and proposes a model to explore the adoption of AI technology for talent acquisition. The survey was conducted among the 562 human resource managers and talent acquisition managers with a structured questionnaire. The analysis of data was completed using PLS-SEM.

Findings

This research reveals that cost-effectiveness, relative advantage, top management support, HR readiness, competitive pressure and support from AI vendors positively affect AI technology adoption for talent acquisition. Security and privacy issues negatively influence the adoption of AI technology. It is found that task and technology characteristics influence the task technology fit of AI technology for talent acquisition. Adoption and task technology fit of AI technology influence the actual usage of AI technology for talent acquisition. It is revealed that stickiness to traditional talent acquisition methods negatively moderates the association between adoption and actual usage of AI technology for talent acquisition. The proposed model was empirically validated and revealed the predictors of adoption and actual usage of AI technology for talent acquisition.

Practical implications

This paper provides the predictors of the adoption of AI technology for talent acquisition, which is emerging extensively in the human resource domain. It provides vital insights to the human resource managers to benchmark AI technology required for talent acquisition. Marketers can develop their marketing plan considering the factors of adoption. It would help designers to understand the factors of adoption and design the AI technology algorithms and applications for talent acquisition. It contributes to advance the literature of technology adoption by interweaving it with the human resource domain literature on talent acquisition.

Originality/value

This research uniquely validates the model for the adoption of AI technology for talent acquisition using the TOE and TTF framework. It reveals the factors influencing the adoption and actual usage of AI technology for talent acquisition.

Fostering ICT use by older workers

Purpose

Adaptation to the requirements of digital economy is especially difficult for older workers, which is a challenge for today’s organizations due to workforce shrinking and ageing. Therefore, the purpose of this paper is to investigate how it is possible to develop older employees’ potential in technology use in the business environment.

Design/methodology/approach

The authors examined how employees at various age perceive barriers during enterprise system (ES) adoption and use. This exploratory study is based on grounded theory and draws from the opinions of 187 Polish ES practitioners.

Findings

With age, emphasis on employees’ perception of mandatory ICT implementation projects is shifting from technology to people-related considerations. For older employees, job security and workload appear the most critical issues in such projects. Age-diverse collaboration appears necessary to address the problems posed by technology-related and demographic changes.

Research limitations/implications

The findings imply that incorporating multiple stakeholder perspectives and age-related considerations into research on ICT adoption appears essential.

Practical implications

ICT adoption in the business environment can be successfully supported by age-balanced team building, cooperation between younger and older employees, and age-adjusted change management initiatives.

Social implications

Supporting older employees during the implementation of mandatory business software should embrace reducing their negative attitudes to ICT-induced change by minimizing their perception of job insecurity.

Originality/value

Unlike many prior studies, the current research places age in the central role and discusses not only how it is possible to support older employees, but also how to leverage their potential in the process of ICT adoption and use in a mandatory setting.

Moderating Effects of Demographics on Green Information System Adoption

The important role of demographics on technology adoption has been highlighted vastly in the literature. Therefore, this study aims at investigating the moderating role of managers’ demographics in their decision-making process to adopt Green information system (Green IS) from the lens of norm activation theory. With 175 valid questionnaires hand collected from organizations’ decision-makers, the researchers examined the research model and its related hypotheses utilizing the Partial Least Squares (PLS)–Structural Equation Modeling (SEM). The results showed Green IS attitude together with personal norm to be the most influential factors, followed by environmental attitude. In addition, we found that while awareness of consequences significantly impacted personal norms, its explanatory power on personal norms was higher when it was mediated through ascription of responsibility. Regarding the moderator variables, the model explained better the pro-environmental behavioral intention of managers towards the adoption of Green IS among older female and well-educated managers. Contributions of the study are further discussed.