{"title":"Intermediating mechanisms and market conditions in big data knowledge management for enhanced market performance","authors":"Junaid Aftab , Feng Wei , Mohit Srivastava , Nabila Abid , Muhammad Ishtiaq Ishaq","doi":"10.1016/j.techfore.2025.124266","DOIUrl":null,"url":null,"abstract":"<div><div>Big data has become a new reality, enabling organizations to gain novel insights and adjust strategies concerning competitors and consumer preferences. However, the hospitality industry still struggles to effectively leverage big data knowledge management to enhance performance and achieve a competitive advantage. Therefore, this study examines the impact of big data knowledge management on market performance, drawing on the knowledge-based view as its theoretical foundation. Additionally, it investigates the mediating roles of big data analytical capability and sustainable marketing in the relationship between big data knowledge management and performance while considering market turbulence as a boundary condition. Using a survey-based research design, data were collected in two waves from 323 managerial-level employees in the Pakistani hospitality industry and analyzed using structural equation modeling. The findings confirm the mediating roles of big data analytical capability and sustainable marketing while revealing that market turbulence weakens the positive association between sustainable marketing and performance. From a theoretical perspective, this study provides empirical support for the proposed hypotheses, offering insights into how big data knowledge management and analytical capability contribute to sustainable marketing and performance in emerging markets. From a managerial standpoint, the findings provide practical guidance for top management on effectively utilizing big data to maximize returns in the hospitality industry.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"219 ","pages":"Article 124266"},"PeriodicalIF":13.3000,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technological Forecasting and Social Change","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0040162525002975","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
Big data has become a new reality, enabling organizations to gain novel insights and adjust strategies concerning competitors and consumer preferences. However, the hospitality industry still struggles to effectively leverage big data knowledge management to enhance performance and achieve a competitive advantage. Therefore, this study examines the impact of big data knowledge management on market performance, drawing on the knowledge-based view as its theoretical foundation. Additionally, it investigates the mediating roles of big data analytical capability and sustainable marketing in the relationship between big data knowledge management and performance while considering market turbulence as a boundary condition. Using a survey-based research design, data were collected in two waves from 323 managerial-level employees in the Pakistani hospitality industry and analyzed using structural equation modeling. The findings confirm the mediating roles of big data analytical capability and sustainable marketing while revealing that market turbulence weakens the positive association between sustainable marketing and performance. From a theoretical perspective, this study provides empirical support for the proposed hypotheses, offering insights into how big data knowledge management and analytical capability contribute to sustainable marketing and performance in emerging markets. From a managerial standpoint, the findings provide practical guidance for top management on effectively utilizing big data to maximize returns in the hospitality industry.
期刊介绍:
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