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1 – 2 of 2Attia Abdelkader Ali, Fernando Campayo-Sanchez and Felipe Ruiz-Moreno
This article examines the impact of banks’ corporate social responsibility communication through social media (CSR-S), electronic word of mouth (eWOM), and brand reputation on…
Abstract
Purpose
This article examines the impact of banks’ corporate social responsibility communication through social media (CSR-S), electronic word of mouth (eWOM), and brand reputation on consumer behavior during the COVID-19 crisis, with a focus on purchase intention.
Design/methodology/approach
The study employed a quantitative approach to analyze data from a survey of 621 Egyptian bank customers who followed the banks’ social media pages and interacted with CSR-S initiatives. A genetic algorithm selected the most relevant variables affecting purchase intention. A Bayesian regression model was used to analyze the impact of CSR-S communication, eWOM, and brand reputation on purchase intention.
Findings
CSR-S initiatives, eWOM, and brand reputation were found to influence customer purchase intention. CSR-S initiatives can boost purchase intention by encouraging brand reputation and initiative sharing with friends and other customers. However, CSR-S negatively moderates the positive impact of eWOM and brand reputation on the predisposition to contract products and services with the bank.
Originality/value
This study addresses critical research gaps in CSR literature. Firstly, it examines the impact of CSR-S actions on customer behavior, a perspective less explored in previous research. Secondly, it investigates the intricate relationships between CSR-S, eWOM, brand reputation, and purchase intention, shedding light on their interplay, particularly during the COVID-19 pandemic. Additionally, this research extends CSR-S investigations to the competitive banking industry and focuses on a developing country context, enhancing the applicability of findings for Egyptian banks. Lastly, the study employs advanced methodologies to improve the accuracy of results.
研究目的
本文擬探討於2019冠狀病毒病危機期間、銀行透過社交媒體而進行關於企業社會責任的溝通 (以下簡稱社媒企社責溝通) 、電子口碑和品牌聲譽,如何影響消費行為; 研究會聚焦於客戶的購買意向上。
研究設計/方法/理念
研究以定量方法、去分析來自涵蓋621名埃及銀行客戶的調查的數據; 這些客戶均有追隨銀行的社交媒體頁面,並曾與銀行就企業社會責任提出的倡議進行互動交流。研究人員以基因演算法挑選了與購買意向相關性最密切的變量,並以貝葉斯回歸模型,去分析探討社媒企社責溝通、電子口碑和品牌聲譽、如何影響客戶的購買意向。
研究結果
研究結果顯示,透過社交媒體傳達的企業社會責任倡議、電子口碑和品牌聲譽,均會影響客戶的購買意向。這類倡議會透過促進品牌聲譽和朋友或客戶間的互相共享而令購買意向提昇。唯社媒企社責溝通會減弱電子口碑和品牌聲譽給客戶購買意向帶來的正面影響,使他們與銀行訂立商品或服務契約的意欲降低。
研究的原創性
本研究致力回應企業社會責任文獻內重要的研究空白。首先,研究人員探討社媒企社責溝通對客戶行為帶來的影響,這研究角度從來沒有被充分利用。其次,本研究探討社媒企社責溝通、電子口碑、品牌聲譽和購買意向之間錯綜複雜的關係,這幫助闡明各元素的相互作用,尤以2019冠狀病毒病肆虐期間為甚。再者,本研究把關於社媒企社責溝通的研究擴展至競爭性銀行業,並聚焦於涉及一個發展中國家的背景,這都使研究結果更能應用於分析埃及銀行上。最後,研究人員為了提高研究結果的準確性,採用了先進的方法進行研究。
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Nehal Elshaboury, Tarek Zayed and Eslam Mohammed Abdelkader
Water pipes degrade over time for a variety of pipe-related, soil-related, operational, and environmental factors. Hence, municipalities are necessitated to implement effective…
Abstract
Purpose
Water pipes degrade over time for a variety of pipe-related, soil-related, operational, and environmental factors. Hence, municipalities are necessitated to implement effective maintenance and rehabilitation strategies for water pipes based on reliable deterioration models and cost-effective inspection programs. In the light of foregoing, the paramount objective of this research study is to develop condition assessment and deterioration prediction models for saltwater pipes in Hong Kong.
Design/methodology/approach
As a perquisite to the development of condition assessment models, spherical fuzzy analytic hierarchy process (SFAHP) is harnessed to analyze the relative importance weights of deterioration factors. Afterward, the relative importance weights of deterioration factors coupled with their effective values are leveraged using the measurement of alternatives and ranking according to the compromise solution (MARCOS) algorithm to analyze the performance condition of water pipes. A condition rating system is then designed counting on the generalized entropy-based probabilistic fuzzy C means (GEPFCM) algorithm. A set of fourth order multiple regression functions are constructed to capture the degradation trends in condition of pipelines overtime covering their disparate characteristics.
Findings
Analytical results demonstrated that the top five influential deterioration factors comprise age, material, traffic, soil corrosivity and material. In addition, it was derived that developed deterioration models accomplished correlation coefficient, mean absolute error and root mean squared error of 0.8, 1.33 and 1.39, respectively.
Originality/value
It can be argued that generated deterioration models can assist municipalities in formulating accurate and cost-effective maintenance, repair and rehabilitation programs.
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