Digitalization in human resource management led to the implementation of Artificial Intelligence (AI) and Neuro Linguistic Programming (NLP) in recruitment practices. However, although AI and NLP were adopted globally, the empirical evidence in emerging countries, especially Pakistan, was scanty. Hence, this study investigated the impacts of individually and jointly implementing AI and NLP on candidate assessment outcomes in the telecommunications industry in Pakistan. According to the literature, this study is grounded in Technological Determinism, Machine Learning Theory, Psycholinguistic Theory, and Cognitive Behaviorism. A quantitative correlational approach was used in this study. To investigate the proposed research questions, descriptive statistics, Pearson correlations, simple regressions, and multiple regressions were conducted using data from 110 recruiters in Pakistan's telecommunications industry, collected via multi-item questionnaires and a stratified purposive sampling method. Internal consistency of all measures was very high. Descriptive analysis indicated highly favorable perceptions of technology-enabled recruitment. Correlation analysis showed that all associations were highly significant and strong. Simple regression revealed that both predictors significantly forecast the outcome measure. Multiple regression indicated that both AI and NLP independently had significant impacts on candidate assessment outcomes. Nonetheless, their joint application lacked additional explanatory power due to their shared variance.
","abstract_html":"<p>Digitalization in human resource management led to the implementation of Artificial Intelligence (AI) and Neuro Linguistic Programming (NLP) in recruitment practices. However, although AI and NLP were adopted globally, the empirical evidence in emerging countries, especially Pakistan, was scanty. Hence, this study investigated the impacts of individually and jointly implementing AI and NLP on candidate assessment outcomes in the telecommunications industry in Pakistan. According to the literature, this study is grounded in Technological Determinism, Machine Learning Theory, Psycholinguistic Theory, and Cognitive Behaviorism. A quantitative correlational approach was used in this study. To investigate the proposed research questions, descriptive statistics, Pearson correlations, simple regressions, and multiple regressions were conducted using data from 110 recruiters in Pakistan's telecommunications industry, collected via multi-item questionnaires and a stratified purposive sampling method. Internal consistency of all measures was very high. Descriptive analysis indicated highly favorable perceptions of technology-enabled recruitment. Correlation analysis showed that all associations were highly significant and strong. Simple regression revealed that both predictors significantly forecast the outcome measure. Multiple regression indicated that both AI and NLP independently had significant impacts on candidate assessment outcomes. Nonetheless, their joint application lacked additional explanatory power due to their shared variance.</p>","abstract_has_math":false,"creators":["FAHIM, AMNA"],"institution":null,"degree_name":"DBA Doctorate in Business Administration","degree_level":"Dissertation - Public Access","degree_discipline":"Business Administration","degree_department":null,"school":null,"contributors":["Dr David San Filippo","Dr Marguerite Chabau","Dr David Ross"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026-06-01T07:00:00Z","date_published":"2026-06-01T07:00:00Z","updated_at":"2026-07-24T03:21:46Z","subjects":["Artificial Intelligence (AI); Neuro-Linguistic Programming (NLP); Candidate Assessment; Recruitment; Talent Acquisition; Human Resource Management (HRM); Machine Learning; Psycholinguistics","Business Administration, Management, and Operations","Diversity, Equity, and Inclusion","Performance Management"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.nl.edu/diss/997","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dr David San Filippo","Dr Marguerite Chabau","Dr David Ross"]},{"key":"dc:creator","label":"Author","values":["FAHIM, AMNA"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2026-06-30T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Business Administration"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation - Public Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["DBA Doctorate in Business Administration"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Artificial Intelligence (AI); Neuro-Linguistic Programming (NLP); Candidate Assessment; Recruitment; Talent Acquisition; Human Resource Management (HRM); Machine Learning; Psycholinguistics","Business Administration, Management, and Operations","Diversity, Equity, and Inclusion","Performance Management"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.nl.edu/diss/997"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Digitalization in human resource management led to the implementation of Artificial Intelligence (AI) and Neuro Linguistic Programming (NLP) in recruitment practices. However, although AI and NLP were adopted globally, the empirical evidence in emerging countries, especially Pakistan, was scanty. Hence, this study investigated the impacts of individually and jointly implementing AI and NLP on candidate assessment outcomes in the telecommunications industry in Pakistan. According to the literature, this study is grounded in Technological Determinism, Machine Learning Theory, Psycholinguistic Theory, and Cognitive Behaviorism. A quantitative correlational approach was used in this study. To investigate the proposed research questions, descriptive statistics, Pearson correlations, simple regressions, and multiple regressions were conducted using data from 110 recruiters in Pakistan's telecommunications industry, collected via multi-item questionnaires and a stratified purposive sampling method. Internal consistency of all measures was very high. Descriptive analysis indicated highly favorable perceptions of technology-enabled recruitment. Correlation analysis showed that all associations were highly significant and strong. Simple regression revealed that both predictors significantly forecast the outcome measure. Multiple regression indicated that both AI and NLP independently had significant impacts on candidate assessment outcomes. Nonetheless, their joint application lacked additional explanatory power due to their shared variance.
"]},{"key":"dc:title","label":"Title","values":["The Impact Of Artificial Intelligence And Neuro-Linguistic Programming On Candidate Assessment In Talent Acquisition"]}]}],"canonical_facts":{"dc:contributor":["Dr David San Filippo","Dr Marguerite Chabau","Dr David Ross"],"dc:creator":["FAHIM, AMNA"],"dc:date.available":["2026-06-30T07:00:00Z"],"dc:description.abstract":["Digitalization in human resource management led to the implementation of Artificial Intelligence (AI) and Neuro Linguistic Programming (NLP) in recruitment practices. However, although AI and NLP were adopted globally, the empirical evidence in emerging countries, especially Pakistan, was scanty. Hence, this study investigated the impacts of individually and jointly implementing AI and NLP on candidate assessment outcomes in the telecommunications industry in Pakistan. According to the literature, this study is grounded in Technological Determinism, Machine Learning Theory, Psycholinguistic Theory, and Cognitive Behaviorism. A quantitative correlational approach was used in this study. To investigate the proposed research questions, descriptive statistics, Pearson correlations, simple regressions, and multiple regressions were conducted using data from 110 recruiters in Pakistan's telecommunications industry, collected via multi-item questionnaires and a stratified purposive sampling method. Internal consistency of all measures was very high. Descriptive analysis indicated highly favorable perceptions of technology-enabled recruitment. Correlation analysis showed that all associations were highly significant and strong. Simple regression revealed that both predictors significantly forecast the outcome measure. Multiple regression indicated that both AI and NLP independently had significant impacts on candidate assessment outcomes. Nonetheless, their joint application lacked additional explanatory power due to their shared variance.
"],"dc:identifier":["https://digitalcommons.nl.edu/diss/997"],"dc:subject":["Artificial Intelligence (AI); Neuro-Linguistic Programming (NLP); Candidate Assessment; Recruitment; Talent Acquisition; Human Resource Management (HRM); Machine Learning; Psycholinguistics","Business Administration, Management, and Operations","Diversity, Equity, and Inclusion","Performance Management"],"dc:title":["The Impact Of Artificial Intelligence And Neuro-Linguistic Programming On Candidate Assessment In Talent Acquisition"],"thesis:degree_discipline":["Business Administration"],"thesis:degree_level":["Dissertation - Public Access"],"thesis:degree_name":["DBA Doctorate in Business Administration"]},"updated_at":"2026-07-24T03:21:46Z"}