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Article
Publication date: 11 June 2024

Hao-Fan Chumg, Sheng-Pao Shih, I-Hua Hung, Wen-Chin Tsao and Jui-Lung Chen

This research explores the complex interplay of multiple social factors with regard to what might encourage or inhibit users to interact with social commerce (SC).

Abstract

Purpose

This research explores the complex interplay of multiple social factors with regard to what might encourage or inhibit users to interact with social commerce (SC).

Design/methodology/approach

To investigate the phenomenon, we developed a model based on goal-directed behaviour and pluralistic ignorance theory (typically generated by universal behavioural adherence to social norms). Based on the 394 valid responses collected from a survey, partial least squares structural equation modelling (PLS-SEM), PROCESS and ANOVA were employed to examine the research hypotheses.

Findings

The results show that pluralistic ignorance and commercial desire positively influence SC intention. More importantly, our results show that the moderating effect of pluralistic ignorance dampens the positive relationship between social subjective norms and commercial desire. The findings also suggest that pluralistic ignorance mediates the relationships between: (1) social identity and SC intentions and (2) fear of isolation and SC intentions.

Originality/value

Consequently, this study reveals that SC intentions result from complex interactions between an individual’s psychology and social phenomena. Theoretical and managerial implications are also discussed to provide for the successful development of strategies regarding SC for researchers and SNSs operators.

Article
Publication date: 8 January 2021

Fahmi Ali Hudaefi and Irfan Syauqi Beik

Despite the COVID-19 recession, the collection of zakat (almsgiving) managed by the National Board of Zakat Republic of Indonesia (BAZNAS RI) has increased, especially during…

2254

Abstract

Purpose

Despite the COVID-19 recession, the collection of zakat (almsgiving) managed by the National Board of Zakat Republic of Indonesia (BAZNAS RI) has increased, especially during Ramaḍān 1441 Hijra. Previous works show a positive relationship between digital zakat campaign and zakat collection. This paper aims to study the means of digital zakat campaign during COVID-19 outbreak. This topic is theoretically and practically important in the emerging debate of Islamic marketing, notably in Islamic social finance field.

Design/methodology/approach

This paper uses a qualitative research approach. A case study is engaged in the selection of BAZNAS RI for a detailed discussion of a zakat organisation. Meanwhile, a netnographic approach is used to analyse the number of 549 posts from BAZNAS RI’s social media, which are Facebook, Instagram, Twitter and YouTube. Furthermore, a qualitative software analysis of NVivo 12 Plus is used in performing the analytical procedures.

Findings

This work explains the means of digital zakat campaign during COVID-19 outbreak with a case of BAZNAS RI. It is identified the number of 6 parent nodes and 64 child nodes from the analysis using NVivo 12 Plus. The authors’ parent nodes are “donation”, “infaq” (Islamic spending for charities), “Ramaḍān matters”, “ṣadaqah” (voluntary charity), “virtual events” and “zakat”. These nodes detail digital campaign of BAZNAS RI posted in its social media during COVID-19 period in Ramaḍān. A theoretical implication of inclusive marketing is derived from the analysis. It explains that the inclusiveness of digital contents is practically significant in campaigning zakat as a religious obligation that contributes to social and financial benefits.

Research limitations/implications

This paper does not claim a positivist perspective on the relationship between digital zakat campaign and zakat collection. Instead, this paper explores in-depth the practice of digital zakat campaign, which the previous study confirms its association with a muzakki’s (Muslims who are obliged to pay zakat) decision to pay zakat.

Practical implications

This paper establishes the Islamic marketing theory that is derived from industrial practices. The inclusiveness of digital contents in zakat campaign is critical in activating zakat as a religious obligation that authentically shapes the social and economic processes of a Muslim community. This theory is practically important for 'amils (employees) of zakat institution who work in the marketing division, chiefly to create such contents to post in social media.

Social implications

The authors’ node of zakat distribution for COVID-19 relief indicates the importance of a formalised zakat institution to actualise zakat’s role in handling socioeconomic problems. Thus, paying zakat formally in an authorised organisation may contribute to a greater social contribution and maṣlaḥah (public interest) than paying it informally without any effective measurement.

Originality/value

This study contributes to the novelty in the Islamic marketing debate within two folds. First, this paper is among the pioneers in studying digital zakat campaign during COVID-19 outbreak by using a netnographic approach. Therefore, a theoretical implication derived from industrial practices is contributed. Second, this paper details the steps in using NVivo 12 Plus to analyse the unstructured data sampled from the internet. The future studies may thus refer to this work to understand the application of netnography and the procedures in analysing data from social media using this software.

Details

Journal of Islamic Marketing, vol. 12 no. 3
Type: Research Article
ISSN: 1759-0833

Keywords

Article
Publication date: 2 February 2022

Deepak Suresh Asudani, Naresh Kumar Nagwani and Pradeep Singh

Classifying emails as ham or spam based on their content is essential. Determining the semantic and syntactic meaning of words and putting them in a high-dimensional feature…

391

Abstract

Purpose

Classifying emails as ham or spam based on their content is essential. Determining the semantic and syntactic meaning of words and putting them in a high-dimensional feature vector form for processing is the most difficult challenge in email categorization. The purpose of this paper is to examine the effectiveness of the pre-trained embedding model for the classification of emails using deep learning classifiers such as the long short-term memory (LSTM) model and convolutional neural network (CNN) model.

Design/methodology/approach

In this paper, global vectors (GloVe) and Bidirectional Encoder Representations Transformers (BERT) pre-trained word embedding are used to identify relationships between words, which helps to classify emails into their relevant categories using machine learning and deep learning models. Two benchmark datasets, SpamAssassin and Enron, are used in the experimentation.

Findings

In the first set of experiments, machine learning classifiers, the support vector machine (SVM) model, perform better than other machine learning methodologies. The second set of experiments compares the deep learning model performance without embedding, GloVe and BERT embedding. The experiments show that GloVe embedding can be helpful for faster execution with better performance on large-sized datasets.

Originality/value

The experiment reveals that the CNN model with GloVe embedding gives slightly better accuracy than the model with BERT embedding and traditional machine learning algorithms to classify an email as ham or spam. It is concluded that the word embedding models improve email classifiers accuracy.

Details

Data Technologies and Applications, vol. 56 no. 4
Type: Research Article
ISSN: 2514-9288

Keywords

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