This study attempts to verify whether green-marketing efforts of companies are recognised by the Polish customer in social media—a vital marketing communication channel. For businesses, this awareness carries important implications for the effectiveness and profitability of the eco-marketing campaigns. This study employed survey methodology, which was coupled with participant observation of online ecology-centred communities. It is shown that the economic aspect of green marketing is valued by customers and they are quite observant with respect to such expressions of eco-marketing as eco-organic product packaging or production in the spirit of zero-waste technology. The results indicate that eco-marketing activities should be predominantly targeted at women because they are more likely to take note of the message. The statistical part of the study utilises the Chi-square (χ2) test (significance level α = 0.05) and the gamma distribution. Eco-marketing activities appear to attract notice in social media, but not yet as much as presumably desired. Gender is shown to correlate with respect to questions regarding the noticeability of zero-waste activities and pro-ecological activities in social media. Women display higher awareness of “zero-waste” and pro-ecological social media campaigns. In the aggregate, those who perceive “zero waste” as a lifestyle include women, who are more observant.
The purpose of this paper is to present the potential of Internet of Things (IoT) for customer data collection for Customer Relationship Management (CRM) systems. The Internet of Things technology finds numerous applications in company operations ranging from scheduling production tasks to supporting marketing activities. This article discusses the possibility of using Internet of Things to collect customer data. Examples have been presented that will allow detection of some dependencies between the use of this technology and the quality of received data, which may be subjected to analyses, inter alia, in the CRM system. There are also examples of solutions that can be successfully used by enterprises that want to process and analyse data about their clients and have difficulty in obtaining this data.
The main purpose of this article is to verify whether the COVID-19 pandemic affects customers’ behaviours. The examined behaviours are: buying Polish products, buying organic products, buying more at one time, paying attention to prices, asking others to go shopping, and shopping online. For this purpose, an online survey was conducted. The questionnaire was completed by 1000 Polish consumers. The collected data were analysed statistically, and it was shown that the COVID-19 pandemic has an influence on consumers’ behaviours. This is particularly visible in paying attention to prices more frequently, more frequent online shopping, and more frequent purchases of larger amounts of products. Consumers are more likely to buy Polish products and organic products. The largest changes in behaviour were observed among women, people aged under 35, people with higher education, and those with the highest incomes per family member. The research identified the group of consumers who more often do online shopping, purchase more products, and more often buy Polish and organic products; this information may be used by commercial enterprises to create sales strategies. It is advisable to develop online sales and to display information about the fact that products are made in Poland, and information about their ecological origin. The value of this article is to identify the impact of the COVID-19 pandemic on consumer behaviour in the organic market in Poland, to identify groups of consumers whose behaviour has changed, and to indicate the directions of those changes.
The work covers the development of intelligent sensors, as well as intelligent mechanisms for the assembly and control of industrial processes using modern measurement techniques, process tomography, vision systems, motion and temperature sensors. Design/Methodology/Approach: Tomographic techniques and new analytical algorithms were used. Special algorithms have been developed to combine data from different types of measurements in real time to identify potential hazards or undesirable effects. Findings: The use of various types of data in a single decision-making process, starting with the availability of resources, availability of staff and ending with the maintenance schedules of machines, will allow for the analysis and optimisation of the process. The use of the socalled uncertain data and data that do not have an unambiguous impact on the production process requires the use of solutions based on artificial intelligence algorithms in the decision-making process, which are able to draw conclusions relatively quickly based on such data, and then quickly affect the optimisation of the production process. The results of the conducted research indicate that a platform with an open architecture can be a useful tool in the control and steering of industrial processes. Practical Implications: A measurement module that allows to unify the signal coming out of particular measurement sub-assemblies to a coherent form, thanks to which the acquisition, storage and processing of any quantity can be carried out in a similar way for each case. Originality/Value: The novelty and innovation of the system is a unique technological solution (types of measurements and data processing), new algorithms for optimisation, reconstruction and data analysis, a unique multi-module device based on tomographic technologies. The project as a whole as well as each of its components is innovative on a global scale. The use of tomography for analysis, control and monitoring of technological processes is an innovative solution.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.