Perceived recourse and redress risk (PRRR): conceptualisation and preliminary scale development

Prior to purchase, consumers expect that retailers are able to handle their complaints and resolve problems effectively. However, consumers’ efforts in seeking proper recourse and redress often end in frustration. This has given rise to consumers’ perceived lack of effective and efficient complaint management systems, creating a barrier to purchasing – this is termed “Perceived Recourse and Redress Risk” (PRRR). This research posited that existing purchase risk dimensions – performance, financial, privacy, physical, psychological, social, time, and convenience risks – do not adequately capture consumers’ PRRR as a barrier to purchase, and formal scales for measuring constructs that are directly central to recourse and redress failures do not exist. This research discovered the types of risk related to consumers’ PRRR and investigated the potentially risky purchase contexts that influence the salience of PRRR. New items were developed to measure these aspects of perceived risk. From the experiments, consumers perceived a higher level of PRRR when they used an interactive complaint channel compared to when they used a remote complaint channel to seek redress; a higher PRRR for online purchases compared to offline purchases; and a higher PRRR for purchases that involved a foreign retailer compared to purchases from a locally owned retailer. Purchase platform and consumers’ level of ethnocentrism did not moderate the impact of both complaint channel and retailer’s country of origin on consumers’ level of PRRR. Dimensions of PRRR such as “Unreturned”, “Transferred”, “Inaction”, and “No Action due to Policy” showed more consistent significant effects than other dimensions such as “Invalid”, “Rudeness”, “Extended Delay”, and “Incompetence”. This research shed light on effective complaint management systems and suggests that certain changes in the way complaints are handled could result in different and more desirable consumer behaviours, so affecting consumer loyalty

The impact of economic indicators, industrialization and pollutant emissions (CO2) on economic development in Malaysia / Saliza Sulaiman ... [et al.]

The main purpose of this research is to identify whether there is any relationship between economic indicators, industrialization and pollutant emissions (CO2) on economic development in Malaysia. Economic indicators consist of government debt, health and education expenditure. This paper used Ordinary Least Square (OLS) Method to test the factors affecting the economic development. The data collection for each variable are collected from year 1980 until 2014 for 35 years in Malaysia. The result of the study shows that industrialization and pollutant emission (CO2) have a significant relationship on economic development. Meanwhile, government debt, health and education expenditure do not have a significant relationship on economic development. These finding will help to understand the effect of independent variables towards the dependent variable (economic development)

The Mediating Role of Incumbent System Habit in the Relationship between Customers Perceived Value and Repurchase Intention in Smartphone Industry in Malaysia

The increasing number of smartphone vendors have made the competition in smartphone industry becomes fiercer than before. The implementation of habit construct in the research model have recently gained increasing attention among the IT researchers. Despite preliminary literatures perceived consumer habit as determinant of repurchase behavior in digital context, majority of the studies have defined consumer habit from the perspective of situation of use, and still lack of research focusing on habit from the perspective of skill developed related to the system. This study therefore aims to provide research model investigating the mediating role of skill-based habit related to the system (incumbent system habit) in the relationship between customer perceived value and customer repurchase intention in smartphone context

Impact of online classes on academic performance of university students during COVID-19

The COVID-19 virus has changed whole system of the world; in education sector, institutions have switched their physical classes to online classes. Though online classes provide students with the opportunity of self-study but it is uncomfortable for many students and has a negative impact on student’s academic performance. Along with academic performance, academic integrity is questioned due to online classes. Therefore, the current study aimed to find out the impact of online classes (independent variable) on Baluchistan University students’ academic performance. A total of 500 university students from five different universities of Baluchistan have been selected to respond the questionnaire online. Results show that online classes have direct effect on academic performance

AUTOMATED NETWORK FAULT INFERENCE TOOL (AN FIT)

The lack of specialized experts in diagnosing network faults, inconsistencies of diagnose results and professional opinions, time-consuming and growing complexity of this task; has motivated the dewlopment of our c\utomated Network Fault Diagnostic System. This system aims to serve as an intelligent diai-,'llOStic system that will be able to produce fast, accurate, user-friendly and appropriate suggestions that will assist normal network users and administrators respectively. To ensure the realistic and successful development of the system, we adopt Extreme Programming methodology. l\lany efforts have been paid to implement a novel and efficient solution to precisely diagnose problems and in timely manner. The methodology has e\·oh-ed from rule-based systems through case-based systems to more recent model-based systems. Our project is designed upon case-based diagnostic approach as it suggests the use of previously experienced, concrete problem or cases instead of rules or modelling yueries evaluation. We propose a system that will provide reactive response on-demand in term of error messages based on inaccessible URL input entered by user. 'I he system will then diagnose the problems based on the formulated inference table that is comprised of pre-defined failure cases and test cases which will be developed via user-defined functions and general network probing tools. hom there, we expect the output to be returned in command line error mess;tges. To measure the success of the system, four Key Performance Indicators (KPI) hm-e been identified as evaluation metrics which are cm·erage, accuracy, time and response. Hence, unit testing, integration testing and usability test will be conducted to obtain the assessment results. We claim that the system could initiate an extensible framework for network services that act as a community support tooL However, at present we narrow down our focus on Web Set\~ce application but by all means encouraging and welcoming the extension to other network services or adding in new test cases as future development for the benefit of all network users

Exploring YouTube Comments to Understand Public Sentiment on COVID-19 Vaccines through Deep Learning-based Sentiment Analysis

COVID-19 was first found in China in 2019. Since then, it has quickly spread around the world, which has led to a lot of news stories and social media posts about the pandemic. YouTube, a popular video-sharing website, has become a valuable source of information on COVID-19 and other topics. However, it can be difficult to extract useful insights from the vast array of user comments that accompany these videos. One potential method for understanding public sentiment is to use sentiment analysis, which involves classifying text as positive, negative, or neutral. In this study, the dataset of over 44,000 YouTube comments related to COVID-19 vaccines was used, which was filtered to a total of 16,073 comments for analysis. The data was cleaned and organised using NeatText and then processed using GloVe word embedding, a technique for establishing statistical relationships between words. Based on the experiment, the performances of three different types of deep learning techniques: recurrent neural networks (RNN), gated recurrent units (GRU) and long short-term memory (LSTM) are compared in accurately classifying the sentiment of the comments. The study found that the GRU had the highest accuracy of 80.19%, followed by the LSTM with 79.00% accuracy, and the RNN with 67.15% accuracy

A Review: Customer Perceived Value and its Dimension

Customer perceived value has become the most extensive used concept in marketing literature in recent years. It is considered as the main key to sustain the business especially in high market competition. Consequently, understanding its dimensions and the influences on customer attitude and behavior becomes crucial for all marketers. This paper reviews the related literatures and categorized dimension of perceived value of durable product into three categories namely product-related value, social-related value, and personal-related value

Use of social media sites by Malaysian universities and its impact on university ranking

Social Media is not just for photo sharing and status update, it can also be used by students for university selection. In the current era of high competition among higher educational institutes, many universities are focusing on online marketing. Most of the students are using social media sites to select their university which shows the importance of online presence for the universities. It is very much important for the universities to decide their marketing strategy to attract more and more international students. Good promotional marketing activities through social media, social networking sites by universities is associated with the ranking of the university. In this article we review the importance of social media marketing through social networking sites like Facebook and the capability of Malaysian universities to use social networking sites and its impact on university ranking and its Facebook engagement rank

Consumer Perceived Value in Understanding Herbal Medicine Consumption: A Conceptual Model

Introduction: Facing extensive competition, the marketers and producers of herbal medicine products (HMP) should pay more concern to maintaining repeat purchases and keeping customers loyal with their products.  Purpose: This study aims to (1) propose the dimensions of consumer perceived value (CPV) for HMP; and (2) propose a conceptual framework to test CPV influences on consumption behavior, repurchase intention and customer loyalty.  Methodology: The value dimensions of HMP included functional value (price), functional value (quality), social value, emotional value (feeling), and conditional value (holistic treatment value).  CPV was proposed as an antecedent of repurchase intention and customer loyalty.  Implications:  A conceptual framework with a second-order multi-dimensional CPV as the antecedent of repurchase intention and customer loyalty was proposed.  This article proposed a conceptual framework to analyze the influence of value dimensions on HMP.  This could provide useful theoretical insights into the values perceived in HMP consumption behavior

The Impact of Economic Indicators, Industrialization and Pollutant Emissions (CO2) on Economic Development in Malaysia

The main purpose of this research is to identify whether there is any relationship between economic indicators, industrialization and pollutant emissions (CO2) on economic development in Malaysia. Economic indicators consist of government debt, health and education expenditure. This paper used Ordinary Least Square (OLS) Method to test the factors affecting the economic development. The data collection for each variable are collected from year 1980 until 2014 for 35 years in Malaysia. The result of the study shows that industrialization and pollutant emission (CO2) have a significant relationship on economic development. Meanwhile, government debt, health and education expenditure do not have a significant relationship on economic development. These finding will help to understand the effect of independent variables towards the dependent variable (economic development