Purchase Intention for Halal Cosmetic Product Among TikTok Application Users in Johor

The demand for halal cosmetic products among the 2.0 billion Muslim consumers is growing internationally. This paper aims to identify the influence on attitude, subjective norms, perceived behavioral control, and knowledge towards the intention to purchase halal cosmetic products among consumers. A total of 100 questionnaires were distributed to TikTok users in Johor. The findings indicated that all variables positively influenced purchase intention of halal cosmetic products. This study also provides further insights into potential marketing strategies by halal cosmetic product manufacturers and the prospective halal cosmetic industry in Malaysia

A survey of AI in operations management from 2005 to 2009

Purpose: the use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing body of publications over the last two decades means that it can be difficult to keep track of what has been done previously, what has worked, and what really needs to be addressed. Hence this paper presents a survey of the use of AI in operations management aimed at presenting the key research themes, trends and directions of research. Design/methodology/approach: the paper builds upon our previous survey of this field which was carried out for the ten-year period 1995-2004. Like the previous survey, it uses Elsevier’s Science Direct database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus, the application categories adopted are: design; scheduling; process planning and control; and quality, maintenance and fault diagnosis. Research on utilising neural networks, case-based reasoning (CBR), fuzzy logic (FL), knowledge-Based systems (KBS), data mining, and hybrid AI in the four application areas are identified. Findings: the survey categorises over 1,400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: the trends for design and scheduling show a dramatic increase in the use of genetic algorithms since 2003 that reflect recognition of their success in these areas; there is a significant decline in research on use of KBS, reflecting their transition into practice; there is an increasing trend in the use of FL in quality, maintenance and fault diagnosis; and there are surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research. Design/methodology/approach: the paper builds upon our previous survey of this field which was carried out for the 10 year period 1995 to 2004 (Kobbacy et al. 2007). Like the previous survey, it uses the Elsevier’s ScienceDirect database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus the application categories adopted are: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Research on utilising neural networks, case based reasoning, fuzzy logic, knowledge based systems, data mining, and hybrid AI in the four application areas are identified. Findings: The survey categorises over 1400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: (a) The trends for Design and Scheduling show a dramatic increase in the use of GAs since 2003-04 that reflect recognition of their success in these areas, (b) A significant decline in research on use of KBS, reflecting their transition into practice, (c) an increasing trend in the use of fuzzy logic in Quality, Maintenance and Fault Diagnosis, (d) surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research. Originality/value: This is the largest and most comprehensive study to classify research on the use of AI in operations management to date. The survey and trends identified provide a useful reference point and directions for future research

A Review of Supply Chain Data Mining Publications

The use of data mining in supply chains is growing, and covers almost all aspects of supply chain management. A framework of supply chain analytics is used to classify data mining publications reported in supply chain management academic literature. Scholarly articles were identified using SCOPUS and EBSCO Business search engines. Articles were classified by supply chain function. Additional papers reflecting technology, to include RFID use and text analysis were separately reviewed. The paper concludes with discussion of potential research issues and outlook for future development

Colour cosmetics consumption among Moroccan women: Examining the Nexus of Attitudes, Religion, and The media

This paper examines colour cosmetic consumption of Morrocan women in relation to the influence of attitudes, religion, and the media. With data from 498 women and using the theory of planned behavior, this study shows that attitude and Perceived behavior control (PBC) affect positively consumer intention to buy colour cosmetics. It also shows that intrinsic or personal religiosity does not affect customer intention to purchase cosmetic products while extrinsic religiosity is negatively correlated to the intention to use these products. Besides, the study demonstrates how different types of media influence the respondents’ consumption of these products. For example, as respondents spend more time watching TF1- the first national French channel - where a more natural look is displayed, the intention to buy color cosmetics decreases by 41.6%. Concerning the socio-demographic factors, the study shows that older women mainly with high income are more likely to consider color cosmetics consumption. The implications of the study are highlighted in the paper

Identifying tourist route patterns using data mining techniques

In this study, researchers applied data mining techniques to reveal tourist route patterns to popular destinations in Surat Thani Province in southern Thailand. Data mining refers to the process of discovering patterns in large data.Two data mining techniques were employed: 1) Cluster analysis was used to identify unique clusters of tourists with common behavioral trends. 2) Association rule mining was used to determine tourist route patterns.From these two data mining techniques, the researchers were able to identify unique clusters of tourists who followed common patterns of travel.The main implications of this study are: 1) that data mining may be used to explain the movement of tourists in any region in the world, and 2) that different facets of the tourism industry can use this information to understand and respond to tourists' needs and interests

Predicting halal cosmetics purchase intention among consumers in Johor Darul Takzim

Although there is a vast and growing number of literature reviews towards the consumer purchase intention, most of these empirical studies were focused more on the conventional purposes rather than purchase intentions for halal cosmetic products. Thus, the objectives of this research are: (1) to identify the influence of attitude, subjective norm, perceived behavioural control, knowledge, safety, and purity towards the intention to purchase halal cosmetic product among consumers, (2) to examine the moderating role of education level between the selected variables (attitude, subjective norm, and perceived behavioural control) and the intention to purchase halal cosmetic product among consumers, and (3) to propose a framework for halal cosmetic products. In this quantitative research study, a structured questionnaire using a 5-point Likert Scale was used as an instrument for the data collection. A total of 400 questionnaires were distributed to consumers in Johor with a response rate of 99.5%. The data was analysed using Partial Least Squares Model Analysis (PLS-SEM). The findings indicated that attitude, subjective norm, perceived behavioural control, knowledge, and purity were found to be positively associated with, and being an influential predictor of purchase intention of halal cosmetic products. Education level was found to be a significant moderator of association between attitude and purchase intention of halal cosmetic products. This study also provides further insights of potential marketing strategies by halal cosmetic product manufacturers, as well as the prospective halal cosmetic industry in Malaysia as a whole

Measuring Customers Satisfaction of E-Commerce Sites Using Clustering Techniques: Case Study of Nyazco Website

Today the use of modern technologies in the daily life for satisfying the needs is unavoidable. Follow the news and searching through the internet has affected organizations to provide platform on the Internet for availability of information for the customers. With the development of e-commerce, online shopping plays an increasingly important role in people’s life. With the use of data mining technique prospect, managers of this site can analyze preferences and purchasing patterns of online customers in order to custom product recommendations. Data mining helps to provide services in accordance with customers’ requirements. The aim of this research is to identify the customers’ requirements in online shopping and cluster these customers based on independent attributes such as gender, product classification, recency, frequency and monetary. For this purpose, the data related to Nyazco website that is an e-commerce website with a variety of products, were examined as a case study in the period of 7 months. The authors of this paper will define four clusters by using k-means algorithm and RFM model by IBM SPSS Modeler 14.2 software. Customers in the third cluster and fourth cluster will be identified as the most important customers. Therefore, providing the demands of these customers should be prioritized

Product Planning techniques: investigating the differences between research trajectories and industry expectations

According to several literature sources, Product Planning is acknowledged as a primary driver of future commercial success for new designed products, and it is schematically constituted by the identification of business opportunities and the selection of most promising alternatives. Despite the recalled relevance of Product Planning, it emerges that a marginal quantity of companies have adopted formal methods to carry out this task. The paper attempts to provide a major understanding about such a limited implementation of Product Planning techniques and other open issues emerging from the analysis of the literature concerning the initial phases of engineering design cycles. The presented study investigates the claimed benefits of methods described in the literature, the level to which such tools are diffused through educational programs in Technical Institutes, the expectations and the demands of a sample of enterprises with respect to new tools supporting Product Planning. It emerges that, whereas existing methods strive to fulfil relevant properties according to the perception of the companies, limitations come out in terms of the transfer of the proposed techniques and their perceived reliability

Consumers’ purchasing behavior – the impact of product innovation

Research Purpose: The main objective of this study is to investigate the way in which consumers’ attitude toward attributes of product innovation influences their purchasing behavior in grocery stores. The study is based on an investigation of the fresh fruit juice category of the F&B industry. Theoretical Framework: The concept of product innovation in the F&B industry is firstly introduced with the aim of providing a broader understanding of its four attributes. This is followed by a description of the TRA model which is widely used to predict consumers’ purchasing behavior before establishing a new model of the way in which product innovation can affect consumers’ purchasing behavior and using it to make a further analysis. Methodology: This thesis is based on qualitative research and the data was collected from semi-structured interviews with eight ICA consumers. Conclusion: The findings show that consumers have an extremely positive attitude toward the different attributes of product innovation because of their beneficial effect. Product innovation generates greater value, which increases their intention to purchase new or improved F&B products. However, not all aspects of the four attributes of product innovation affect consumers’ purchasing behavior and the findings of this study are expected to assist manufacturers and retailers to develop the most useful of them in order to enhance consumers’ purchasing behavior and thereby increase their competitive advantage in the field of grocery marketing