The effect of Technological, Organizational, Environmental, and Task Technology fit on the Adoption and usage of artificial intelligence (AI) for talent acquisition (TA): Evidence from the Pakistani banking sector.

2021 ◽  
Author(s):  
Alina Shakeel ◽  
Danish Ahmed Siddiqui
Keyword(s):  
Artificial Intelligence ◽  
Banking Sector ◽  
Task Technology Fit ◽  
Talent Acquisition ◽  
And Task

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

2020 ◽  
Vol 27 (9) ◽  
pp. 2599-2629
Author(s):  
Rajasshrie Pillai ◽  
Brijesh Sivathanu
Keyword(s):  
Technology Adoption ◽  
Human Resource ◽  
Relative Advantage ◽  
Human Resource Managers ◽  
Content Type ◽  
Actual Usage ◽  
Resource Managers ◽  
Task Technology Fit ◽  
Talent Acquisition ◽  
And Task

PurposeHuman 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/approachThis 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.FindingsThis 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 implicationsThis 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/valueThis 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.

scholarly journals Employee Branding and Talent Acquisition- an Imperative Need

2019 ◽  
Vol 8 (12S2) ◽  
pp. 410-414
Keyword(s):  
Business Enterprise ◽  
Important Stage ◽  
To Come ◽  
Talent Acquisition ◽  
And Task

within the triumphing enterprise age, affiliations want to rehash and to rethink themselves at an important stage and to come to be agiler. advancement of HR the officers proposes a circulate from massive mindset on place of business closer to duty, gaining knowledge of and improvement of marketers and task for capability. The belief driving this examination is to study the affiliation between the worker Branding and expertise Acquisition. The expressive research configuration is used for the present paintings. An top notch inspecting has been used to deliver collectively the facts. The individuals inside the review are 180 HR directors of picked IT groups in Bangalore. The device used for statistics aggregation is a self-specific,self-figured and organized poll. After the assessment, it very well can be presumed that worker Branding decidedly impacts talent Acquisition. The examination famous that in an open ability economic machine, business enterprise emblem is noteworthy in deciding on and maintenance, and protection of excessive functionality experts and should be revolved around gaining knowledge of and administration development, adaptability, prizes and competency systems. A part of the inspiration reliant on the exam is also shown in this paper.

Examining internet banking user’s continuance intention through the lens of technology continuance theory and task technology fit model

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Samar Rahi ◽  
Mazuri Abd Ghani
Keyword(s):  
User Satisfaction ◽  
Internet Banking ◽  
Perceived Usefulness ◽  
Matrix Analysis ◽  
Research Model ◽  
Continuance Intention ◽  
Content Type ◽  
Task Technology Fit ◽  
And Task ◽  
Expectation Confirmation

Purpose The long-term success of internet banking (IB) services is connected with continuous use. Therefore, examining factors which influence IB user continuance intention is important. Grounded in technology continuance theory, bank transparency and task technology fit (TTF) model, the purpose of this study is to develop a unified technology continuance model to investigate IB user continuance intention. Design/methodology/approach The research model was empirically tested with 348 responses. Respondents included in this study had prior experience with IB services. For hypotheses testing, the structural equation modelling approach was used. Findings Findings indicate that the research model has substantial power in explaining IB user continuance intention. Importance performance matrix analysis revealed that bank transparency had the highest importance in determining IB user continuance intention. Therefore, factors like user satisfaction and perceived usefulness have shown a medium level of importance in determining IB user continuance intention. Satisfaction is influenced by perceived usefulness and confirmation and established a significant impact on IB user continuance intention. Practical implications The findings of this research are useful for bank managers and policymakers to develop and design IB services according to user’s expectations. Results demonstrate that expectation confirmation and perceived usefulness are antecedents of IB user satisfaction and IB user continuance intention. In addition to that bank, transparency has shown a significant effect on user expectation and IB user continuance intention. These findings established that accuracy in sharing bank information and clarity in transaction charges encourage the user to continue the use of IB services. Originality/value The current study develops a unified technology continuance model based on the TTF model and technology continuance theory and investigates IB user continuance intention. Moreover, bank transparency is added in the technology continuance model and established a significant impact towards user expectation confirmation and continuance intention. These findings contribute to the limited body of research in the context of IB user continuance intention and enrich information system literature.

Artificial Intelligence in the Banking Sector: Opportunities and Challenges

2021 ◽  
pp. 81-97
Author(s):  
Galina Semeko ◽  
Keyword(s):  
Artificial Intelligence ◽  
Banking Sector ◽  
High Tech ◽  
The World ◽  
The Face

The article deals with the problems of using artificial intelligence technologies in the banking sector in the world in general and in Russia in particular. Characterizes the potential of artificial intelligence technologies and their role in increasing the competitiveness of banks in the face of in Creasing competition from new high-tech financial providers. Presentes an analysis of the factors hampering the introduction of artificial intelligence technologies in banks.

Artificial Intelligence Inroads Into HR

2022 ◽  
pp. 231-246
Author(s):  
Swati Bansal ◽  
Monica Agarwal ◽  
Deepak Bansal ◽  
Santhi Narayanan
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Human Resources ◽  
Generation Y ◽  
Industry 4.0 ◽  
Career Aspirations ◽  
Work Life ◽  
Human Decision ◽  
The Right ◽  
Talent Acquisition

Artificial intelligence is already here in all facets of work life. Its integration into human resources is a necessary process which has far-reaching benefits. It may have its challenges, but to survive in the current Industry 4.0 environment and prepare for the future Industry 5.0, organisations must penetrate AI into their HR systems. AI can benefit all the functions of HR, starting right from talent acquisition to onboarding and till off-boarding. The importance further increases, keeping in mind the needs and career aspirations of Generation Y and Z entering the workforce. Though employees have apprehensions of privacy and loss of jobs if implemented effectively, AI is the present and future. AI will not make people lose jobs; instead, it would require the HR people to upgrade their skills and spend their time in more strategic roles. In the end, it is the HR who will make the final decisions from the information that they get from the AI tools. A proper mix of human decision-making skills and AI would give organisations the right direction to move forward.

Artificial intelligence (AI) applications in Islamic finance and banking sector

2021 ◽  
pp. 108-121
Author(s):  
Adel Sarea ◽  
Mustafa Raza Rabbani ◽  
Md. Shabbir Alam ◽  
Mohammad Atif
Keyword(s):  
Artificial Intelligence ◽  
Banking Sector ◽  
Islamic Finance
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