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Publication date: 24 September 2024

Sukanya Wareebor, Chompoonut Suttikun and Patcharaporn Mahasuweerachai

Consumer behavior is evolving rapidly due to the increasing role of technology in daily life. Online food ordering has emerged as a key channel in this changing landscape. This…

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Abstract

Purpose

Consumer behavior is evolving rapidly due to the increasing role of technology in daily life. Online food ordering has emerged as a key channel in this changing landscape. This paper investigates the relationships between online promotions, consumer skepticism, information sharing on social media and the intention to purchase food and beverages through online delivery services.

Design/methodology/approach

Measures were developed based on a review of existing literature. Data from 402 participants were analyzed using Structural Equation Modeling (SEM).

Findings

The study reveals that online promotions significantly impact consumers' sharing of restaurant posts. Additionally, consumer skepticism about online food sales affects both their sharing behavior and their intention to purchase online. Engagement in sharing restaurant posts online is a strong predictor of online food purchasing intentions.

Practical implications

The findings offer valuable insights for restaurant operators, policymakers and technology developers in the competitive online food delivery sector. They emphasize the importance of implementing innovative promotions and crafting appealing food presentations. These strategies can accelerate customer decision-making, attract new customers and contribute to market expansion and customer base sustainability.

Originality/value

This research provides significant insights for restaurant owners and contributes to the limited literature on online promotions, consumer skepticism and information sharing in the restaurant industry. It also lays the groundwork for future studies aimed at deepening understanding in this field.

Details

Journal of Hospitality and Tourism Insights, vol. 8 no. 3
Type: Research Article
ISSN: 2514-9792

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Article
Publication date: 14 January 2025

Abdullah Al Mamun, Mohammad Nurul Hassan Reza, Qing Yang and Norzalita Abd Aziz

Implementing big data analytics (BDA) for supply chain ambidexterity (agility and adaptability) and green supply chain (GRSC) presents various organizational challenges. These…

117

Abstract

Purpose

Implementing big data analytics (BDA) for supply chain ambidexterity (agility and adaptability) and green supply chain (GRSC) presents various organizational challenges. These include leveraging BDA capabilities to balance agility and adaptability, integrating this combined approach with GRSC and aligning these efforts to enhance firm performance. This study explores the associations between BDA, supply chain agility and adaptability, GRSC and their impact on firm performance.

Design/methodology/approach

Incorporating a resource-based view and contingency theory, we developed a research framework and validated it with data from 355 Chinese firms. Partial least squares structural equation modeling was used to analyze the data.

Findings

The findings demonstrate that BDA capabilities had direct impact on supply chain agility and adaptability, GRSC and firm performance. Moreover, the combination of supply chain agility and adaptability affected GRSC; which in turn significantly influenced firm performance. Supply chain agility and adaptability mediated the relationship between BDA capabilities and GRSC. Additionally, GRSC mediated the relationship between BDA capabilities, supply chain agility and adaptability and firm performance.

Originality/value

This study offers both a theoretical and empirical examination of the relationships between BDA capabilities, supply chain agility and adaptability, GRSC and firm performance. By assessing the direct and mediating effects of these factors on China’s industrial sector, it presents new theoretical and practical insights into BDA and GRSC, thereby enhancing the value of the existing literature.

Details

Journal of Enterprise Information Management, vol. 38 no. 2
Type: Research Article
ISSN: 1741-0398

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