Artificial Intelligence Capabilities and Organizational Sustainability of Retail Outlets in Port Harcourt: A Drive for Renewable Hope in Smart Economies

Abstract

The study examined artificial intelligence capabilities and organizational sustainability of retail outlets in Port Harcourt. The objectives of the study were to examine the relationship between dimensions of artificial intelligence capabilities such as CCTV analytics, chatbots and automated processing; and measures of organizational sustainability in terms of Environmental sustainability and Economic sustainability of retail outlets in Port Harcourt. Thus, the study was anchored on Diffusion of Innovation theoretical foundation. The study adopted the cross-sectional survey research design. The accessible population of the study was Sixteen (16) retail outlets currently operating in Port Harcourt. The entire population was used as the study sample. Thus, the study was census research which involves using the entire population rather than drawing a sample from it. Structured questionnaire served as the instrument for data collection. A total of sixty-four (64) copies of the validated questionnaire were distributed to the targeted audience. The researcher was able to retrieve fifty-six (56) copies of the entire validated questionnaire distributed. Arithmetic mean and standard deviation were used for the research question analyses, while the test of hypotheses was done using Spearman rank order correlation with the aid of SPSS Version 24.0. It was found that there is a significant positive relationship between artificial intelligence capabilities and organizational sustainability of retail outlets in Port Harcourt. It was concluded that leveraging artificial intelligence powered tools such as CCTV analytics, chatbots and automated processing, retailers can enhance operational efficiency, improve customer experiences and gain valuable insights into market trends.  Consequently, it was recommended that operators of retail outlets should utilize automated system to track inventory level, reduce waste and optimize stock replenishment.