Be Muslim Buy from Muslims: Impact of Retailers Religious Orientations on Consumers Purchasing Patterns

Purpose: This study investigates the impact of retailers’ religious affiliation and religiosity on consumers’ purchasing patterns. The moderated mediation model of this study contemplates a) the mediating role of buying motives of consumers based on thoughts, feelings, emotions, which help them make decisions, and b) the moderating role of intrinsic and extrinsic religiosity dimensions. Design/Methodology/Approach: Data were obtained from consumers from metropolitan cities of Pakistan. Simple Linear Regression and Pearson Correlation Coefficients were used to investigate the relationships with the help of SPSS and AMOS software. ArcMap was used to represent the selected sample size. Findings: Drawing on the belief-congruence theory, the findings of this study suggest that religious affiliation of the retailer (RAR) has a significantly positive impact on consumer purchase intentions (CPI) and that consumer buying motives (CBM) have a strong mediating role between RAR and CPI. The study also reveals that the impact of CBM on CPI is stronger in consumers with high intrinsic religiosity. However, data analysis shows that consumers’ extrinsic religiosity is not a significant moderator of the relationship between consumers’ buying motives and purchase intentions. Implications/Originality/Value: The findings of this study can help retailers make better policies to attract consumers and sustain their businesses.

Be Muslim Buy from Muslims: Impact of Retailers Religious Orientations on Consumers Purchasing Patterns

Purpose: This study investigates the impact of retailers’ religious affiliation and religiosity on consumers’ purchasing patterns. The moderated mediation model of this study contemplates a) the mediating role of buying motives of consumers based on thoughts, feelings, emotions, which help them make decisions, and b) the moderating role of intrinsic and extrinsic religiosity dimensions. Design/Methodology/Approach: Data were obtained from consumers from metropolitan cities of Pakistan. Simple Linear Regression and Pearson Correlation Coefficients were used to investigate the relationships with the help of SPSS and AMOS software. ArcMap was used to represent the selected sample size. Findings: Drawing on the belief-congruence theory, the findings of this study suggest that religious affiliation of the retailer (RAR) has a significantly positive impact on consumer purchase intentions (CPI) and that consumer buying motives (CBM) have a strong mediating role between RAR and CPI. The study also reveals that the impact of CBM on CPI is stronger in consumers with high intrinsic religiosity. However, data analysis shows that consumers’ extrinsic religiosity is not a significant moderator of the relationship between consumers’ buying motives and purchase intentions. Implications/Originality/Value: The findings of this study can help retailers make better policies to attract consumers and sustain their businesses.

Deep Learning Approach of Product Evaluation Using Comment Analysis

Digital reviews now play a critical role in strengthening global consumer communications and influencing consumer purchasing patterns. Consumers can use e-commerce giants like Amazon, Flipchart, Snap deal, Jio and others to share their experiences and provide real insights about the performance of a product to future buyers. The classification of reviews into positive and negative sentiment is required in order to derive relevant insights from a big set of reviews. Comment Analysis is a computer programme that extracts subjective data from text. Out of Various Classification models Deep Learning Approach of Product Evaluation Using Comment Analysis is to develop a model that uses AI technologies like Deep Learning to process thousands and millions of online reviews on a product in a split second of time and rate the products on a scale of 1-5 based on the user comments We have worked on two deep learning models based on Recurrent Neural Networks (RNN) and Graph Convolution Network (GCN). Keywords: LSTN, GCN, NLTK

Alcohol Consumption during the COVID-19 Lockdown Period: Predictors of At-Risk Drinking at Different AUDIT-C Cut-Off Thresholds

During the COVID-19 pandemic, alcohol consumption was largely confined to drinking in the home. There has been little research examining variables associated with risk in home drinking. The study employed an online survey of (n = 1128) individuals who had been recruited for their face recognition skills (n = 838, 70.9% females, mean age 45.05 (12.3 SD)). The main dependent variables were three different AUDIT-C cut-off scores for at-risk drinking: (a) 5 for both genders as recommended by Public Health England, (b) 7 for females and 8 for males (cut-off for students and young people) and (c) 8 for both genders (individuals seeking online help for their drinking). Among the independent variables were gender and age, motivations for home drinking using the Home Drinking Assessment Scale (HDAS), purchasing patterns, context of drinking and health and wellbeing. The predictors following hierarchical logistic regressions were for (a) purchasing alcohol online or at a supermarket and emotional HDAS scores, (b) purchasing alcohol online or at a supermarket and for parties, drinking alone and with other members of the household and emotional and practical reason HDAS scores, (c) as for b with the addition that men were more likely to be at-risk drinkers. At-risk drinking in the pandemic was explained by motivational reasons, purchasing patterns and situational factors.

E-Commerce And Showrooming: How Retail is Changing

Distribution channels are undergoing a radical change. The success of the online channel and digitalization driven by a few leading companies in recent years has dramatically changed the way people live and change their purchasing patterns. New technologies have multiplied the points of contact; broadband connection has increased the number of always-on consumers and, at the same time, has developed online shopping (Pentina & Hasty, 2009). What are the implications of digital technological innovations? Will the physical store continue to play a key role? Will online shopping be able to offer an engaging and exciting consumer experience? For example, showrooming is becoming a common practice. It consists in obtaining all relevant information about a product at the point of sale and finally, buying it online. This practice is often used in order to save money since online prices are known to be lower than in retail shops. It is also driven by the customer's need to touch a product before buying it. More and more retailers are dealing with this phenomenon of being a storefront, providing information, letting people touch products and eventually making fewer sales.

Health Star Ratings and Beverage Purchase Intentions: A Study of Australian and New Zealand Hospitality Consumers

This study examines the effects of a health star rating system on the attitudes of consumers and their purchase intentions towards beverage products sold in hospitality venues. Previous studies linking health ratings to the food and beverages of consumers mainly focus on fast-moving consumer goods and retail purchasing. However, purchasing patterns in hospitality and foodservice environments are distinct as consumers may be less concerned about health and more interested in the dining experience. Thus, this research focuses on: (1) whether the presence of health star ratings on beverage products influences the willingness of consumers to purchase in the context of the hospitality industry, and (2) identifying the demographic and psychographic factors influencing these behavioural intentions. Using Ordinary Least Squares regression to analyse data from an e-survey of 1021 consumers in Australia and New Zealand, the study found that health star ratings do have an impact on the willingness of consumers to purchase healthy beverages. Specifically, psychographic segmentation around ‘health goals’ is far more pertinent to understanding purchase behaviour in a hospitality setting than age, gender, income, or country. The findings present new insights into the importance of health star labelling on beverages and the purchase intentions of consumers.

SIKAP DAN KEPUASAN KONSUMEN DALAM PEMBELIAN BOLEN PISANG CV MAYANG SARI DI KOTA BANDAR LAMPUNG

This study aims to determine attitudes, purchasing patterns and customer satisfaction on banana bolen CV Mayang Sari. This research method uses a survey method. Samples of this study consisted of 40 consumers who had purchased and / or consumed banana bolen 3 times. The data analysis methods used were descriptive, Fishbein's Multi-attribute model, Customer Satisfaction Index (CSI) and Importance Performance Analysis (IPA). The attributes used in this study are price, taste, flavor variants, size, texture, product packaging, and accessibility). The results showed that consumers liked banana bolen or had a good attitude with an Ao value of 132.52, the pattern of buying banana bolen CV Mayang Sari by 52.50 percent consumers, namely two boxes (20 pieces) of banana bolen in one transaction with the flavor variant that consumers are most interested in is chocolate 55 percent. The frequency of consumer purchases is 90 percent made once a month, customer Satisfaction Index (CSI) in consuming banana bolen CV Mayang Sari is in the very satisfied criteria, which is equal to 83.82 percent. Based on Importance Performance Analysis (IPA), there is one attribute that falls into quadrant I (Main Priority), namely the taste attribute. In quadrant II (Maintain Achievement) there is one attribute, namely the price attribute, while in quadrant III (Low Priority) there are attributes of size and ease of obtaining products, and in quadrant IV (Excessive) there are several attributes, namely texture, flavor variants, and product packaging.Key words: attitude, banana bolen, CSI, IPA

The Effects of the COVID-19 Pandemic on the Mass Market Retailing of Wine in Italy

The purpose of this study was to provide a detailed framework of wine purchases in supermarkets during the COVID-19 pandemic. The unexpected diffusion of the virus and the restrictions imposed in Italy to prevent its spread have significantly affected the food purchasing habits of consumers. By analyzing the scanner data of the wine sales in the Italian mass market retail channel, this study was intended to show whether and how the dynamics triggered by the pandemic have modified the overall value and type of wine purchases, focusing on prices, formats, and promotional sales. In particular, this study explores sales in two separate periods, namely March–April (the “lockdown”, with general compulsory closing and severe restrictions) and June–July 2020 (the “post-lockdown”, in which some limitations were no longer effective). The analysis of wine sales during lockdown and post-lockdown and the study of the variations compared to the sales of the previous years showed some significant changes in purchase behavior. The results could provide managers, researchers, and policy makers with extensive insights into the purchasing patterns of consumers during this unprecedented time and reveal trends that may characterize the structure of the future wine demand.