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It is no doubt that now a day's Artificial intelligence (AI) is anemergent technology in the digital marketing industry. Commercial Artificial Intelligence (AI) is an important topic for research. Artificial intelligence is growing quickly more sensitive and popular in the digital marketing field due to the capacity of advertisers to employ it efficiently. In order to provide the capability of the highest level of originality and efficiency in digital marketing ground, artificial intelligence techniques are more fruitful for customers, marketers and, retailers. This paper depicts the impact of artificial intelligence techniques on advertising on a diminutive and average scale in the digital marketing field. Ad targeting, predictive analysis, voice search are different artificial intelligence techniques for digital marketing purposes throughout the consumer life cycle. The topic of Artificial Intelligence (AI) in digital marketing itself can be outsized enough to verifyeliminating the area of research into precise application and application frameworks.However, our objective in this paper is to provide a comparative analysis of the digital marketing field using artificial intelligence techniques and to propose some specific guidelines based on different parameters, tools, and frameworks.Through this paper, we have observed thelast five years (2016-2021) research trends which reflect that out of different parameters, customer relationship and promotional activity are the most widely used parameter in the digital marketing field. Another significant point is, most of the research identifies that artificial intelligence is a compulsory technique used in the modern digital marketing field. Some data collection and data analysis tools are also being used in this field using artificial intelligence techniques. Our research methods try to get a complete view on artificial intelligence (AI) Marketing were multifaceted but were very focused on secondary research sources. Finally in this paper, we propose some recommendationsthat will offer better Artificial Intelligence (AI) implementation in the digital marketing field. [ABSTRACT FROM AUTHOR]

In this paper we discuss how digital transformation in finance is leading to increased focus on customer-centricity. We describe how this is often understood as data-driven innovation based on quantitative collection and analysis of digital customer information. We explore the potential of using qualitative data to understand customer contexts and pain points. We share research that illustrates how quantitative data can overlook important knowledge about customers' decision-making and customers' use of different financial solutions, while it can underestimate customers' ability to manage new technological solutions. We recommend that financial service providers extend their innovation toolbox to include qualitative research methods and that they build a customer centric research culture. We also recommend including customers and partners in innovation practices. [ABSTRACT FROM AUTHOR]

The availability of reliable power supply at reasonable cost is important for economic growth and development of a country. Low system reliability leads to increased outages resulting more losses to business sectors. To evaluate such losses customer survey approach was adopted as the customer is in the best judge of losses affected by the outages. The study was conducted to establish monetary losses associated with aftereffects of outages. The Customer Damage Function (CDF) approach was used in this study. The CDF value comes out to be Rs. 16.65 [ABSTRACT FROM AUTHOR]

This paper studies a facility location problem within a closed-loop supply chain framework using discrete-event simulation. The growing pressure on the environmental impact from consumers, governments, and non-governmental organisations has led companies to take responsibility in product recovery processes. This paper integrates CO2 emission as one of the environment considerations into the simulation model. The aim of this paper is to find the best configurations of locating collection centres that will minimise both total logistical costs and total emissions. Three scenarios were proposed to simulate on finding the best collection centres' location. Preliminary experiments were conducted using Exeter city geographical area. The results show that Scenario Two produces the lowest total costs as well as total emissions. Future research directions are also highlighted. [ABSTRACT FROM AUTHOR]

The aim of this study was to show what was caused by Covid-19 at all stages of the food supply chain, whose actors are: producers, processors, distributors, retailers and consumers. Likewise, it sought to identify the main problems and the response actions of each link in the face of the new conditions of the pandemic; for this, a systematic review of the literature was carried out, which was based on the collection of knowledge regarding Covid-19 and the food supply chain. As a result of this search, 67 papers from reliable databases were collected, databases such as Scopus and Web of Science; these papers were considered because they met the stipulated inclusion criteria. The selected papers allowed to identify that the main problems in the links are due to the shortage of labor / workforce, difficulty in the supply of materials or inputs, lack of transportation to distribute food and products, fluctuation in demand and price increases. Regarding the first links, it is identified that the majority of response actions were deeply linked to technology, innovation, IoT, automation and optimization, seeking to reduce the involvement of labor; and, in the case of the consumer link, the response actions were linked to the use of virtual platforms. These responses were adapted in various ways depending on the link, since each of them acted differently to each problem; despite this, the decisions to be made should consider the repercussions they would have on the next link. [ABSTRACT FROM AUTHOR]

This article presents several conference paper abstracts on technology and innovation management, including and examination of whether varieties of capitalism theory properly describes the empirical world of technological innovation, a framework for exploring why industry incumbents lose their leadership positions to attackers in the face of seemingly innocuous technological changes, and empirical research into the nature of business relationships, knowing and learning in the British and Italian motorsport industries.

This paper presents a predictive model for the detection of new customers of the natural gas service distributed by network that have not completed the connection process but are consuming the service without being billed. The CRISP-DM methodology was used to achieve this purpose. First, the process of managing gas service connection requests for new customers was understood; then, customer data and data associated with each stage of the process were identified, as well as an indicator of atypical customers who were disconnected from the service once it was detected that they were consuming without having completed the process. In this way, a dataset was obtained with a total of 6020 requests processed between 2020 and 2022. Algorithms such as Regularized Logistic Regression, Partial Least Squares (PLS) regression and Extreme Gradient Boosting (XGBoost) were used. Once the models were evaluated, XGBoost obtained the best metrics with an Accuracy of 82% and an AUC-ROC curve was 93.6%. For the interpretation of the results, the SHAP values were used, which made it possible to establish that the most relevant variables for detection are: the time spent by the request in the connection process, the geographical location of the customer and the stages that the request fulfills within the connection process. Finally, it is possible to conclude that the results improved the ability to detect those clients that should be checked or disconnected from the service. In future work, the accuracy of the model could be improved through field validation of the predictions and the addition of external variables to the process. [ABSTRACT FROM AUTHOR]

This paper applies a proposed concept of underlying consumer purpose and psychological bonding to the entrepreneurial hospitality industry, including hotels, restaurants, and bed and breakfast establishments. Since the worldwide COVID-19 pandemic, the industry has seen a huge surge in pent-up demand. Event planners' expectations have risen. Students are flocking to the industry where there is almost a guaranteed employment upon graduation. The hospitality industry, being one of the largest industries worldwide, faces intense market competition. To succeed, it relies on various factors, including customer satisfaction, loyalty, trust, affective commitment, and share of wallet The model applied in the paper has recently been published in the Journal of Asia-Pacific Management. The model synthesizes multiple theories, that includes need fulfilment theory, goal theory, and congruency theory. The purpose of this paper is to illustrate that a comprehensive understanding of consumers' needs, goals, values, and self-image is crucial for marketers to enhance service experiences, achieve sustainable success, and help consumers attain their desired psychological outcomes. To combat this somewhat sceptical view of service mix development benefitting the hotel firm primarily, we propose the need to broaden hotel marketing and innovation strategies to include recognition of purposeful fulfilment of consumers' psychological needs/tasks, goals, values, and self-concept. Doing so will strengthen the organizational commitment to hotel consumers, leading to sustainable success for the hotel firm and other hospitality-related businesses. To exemplify further the usefulness of consumers' underlying purpose, we have supplied a variety of hotel examples in figures that demonstrate how hotels can create innovative products or services by utilizing a single meaningful purpose to communicate distinct competencies in meeting consumers' psychological needs and goals and asserting values congruence and self-image congruity. These easy-to-understand models can be applied to the hospitality industry. The paper includes examples and illustrations throughout. Implications for future research and further applications are discussed. [ABSTRACT FROM AUTHOR]

The retail industry has become smarter day by day and providing greater value to both consumers and retailers. Augmented Reality has appeared as a fast development technology used both in physical and online retail to improve the experience of shopping and sale of products. This research paper primarily attempts to identify and analyses increased reality applications in physical and online retail, and the value provided to consumers and retailers. A narrative literature review approach has been adopted for the study using the academic documents published in peer-reviewed scientific journals, white papers, articles, and literature search. This paper is equipped with a general description of the theme that is relatively new, but appears drastically which has not been examined yet. It fosters areas for additional analysis and profit for retail scholars and practitioners. This research also provides retailers important practical implications of AR technology. [ABSTRACT FROM AUTHOR]

Sustainability is not a new trend, but a mandatory measure for responsible and environmentally conscious use of resources. The digital transformation offers new potential in engineering and competitive advantages for companies through innovative technologies like the digital twin. Based on digital twins, products can be optimized, and new business models can be developed. Long-term added value is generated for manufacturing companies and customers. This paper explores the benefits of digital twins in the context of sustainability. Current challenges and use cases of digital twins are analysed. [ABSTRACT FROM AUTHOR]

This paper aims to illustrate the potential positive effects of Chinese nationalism on foreign countries. It manifests that nationalism might be used as a strategic tool: decreasing hostility from Chinese consumers and using the culture-mixing strategy to legitimize the Chinese market. [ABSTRACT FROM AUTHOR]

Countries are increasingly seeking access to reliable, secure and resilient supplies of the critical minerals they need. High technology products including EU critical raw materials (CRMs) are not efficiently recycled and their lifetime can be relatively short. This paper explores new sustainable value creation models in cities for increasing the circularity of selected high technology products containing CRMs. The focus in this paper is on CRMs in smart buildings and their renewable energy solutions. The aim is to provide insights for improving the resilience of critical raw materials and to generate proposals for sustainable value for involved private and public stakeholders. It includes mapping the value chains of selected CRMs containing products and based on the 9R framework (Refuse, Rethink, Reduce, Reuse, Repair, Refurbish, Remanufacture, Repurpose, Recycle and Recover), we create an understanding on the value optimization and operationalization of the chosen R strategies involving public, private organisations and consumers. [ABSTRACT FROM AUTHOR]

Customer Churn Prediction in Banking Sector is the most research area in past few years. Nowadays there isvarious options available for customer in banking sector, where to put money. It is important to gain Customer satisfaction and to maintain bank-customer satisfaction relationship with customer. Generally, if a client stops mistreatment the services of an organization for an extended amount of your time (which varies looking on the merchandise or services of the company), such a client is taken into account churned. In this research paper, a method is proposed to to anticipate client stir in financial area using Machine Learning Algorithms with PCA. In this study Support Vector Machine (SVM), Random Forest Classifier (RFC), Linear Regression (LR), Principal Component Analysis (PCA), Feature selection technique are used to find most relevant features. The dataset is taken from Kaggle. After preprocessing of dataset, the dataset is cleaned from the noisy data. And the dataset is ready for the training process. Now the algorithms are used to train the model. In this using PCA with SVM, PCA with RFC, PCA with LR, Accuracy is measured using confusion matrix. As a result, applying PCA with SVM gives high accuracy as compared to others models. [ABSTRACT FROM AUTHOR]

Socially responsible marketing has become an increasingly important aspect of modern business as companies seek to align their operations with societal expectations and values. This shift towards more socially conscious business practices has been driven by various factors, including changing consumer attitudes and expectations and heightened awareness of environmental and social issues. One industry that has been actively embracing this trend is the cosmetics industry, which must meet evolving customer expectations to remain competitive. This paper explores the concept of socially responsible marketing in the cosmetics industry and demonstrates how companies in this sector adapt to new business challenges and changing societal norms. The paper discusses the role of social performance reporting in the cosmetics industry. It highlights the importance of measuring and reporting companies' impact on all aspects of society, including economic, social, and environmental. This is critical for companies to demonstrate their commitment to socially responsible practices and ensure that their operations are truly sustainable in the long term. The paper also provides valuable lessons for researchers and practitioners. It offers a roadmap for other companies looking to develop more sustainable and socially conscious business models. It brings several valuable insights for researchers interested in socially responsible marketing and the cosmetics industry. Researchers can gain valuable insights into successful strategies and potential challenges associated with implementing socially responsible marketing initiatives by investigating how specific companies in the cosmetics industry adapt to these changes. [ABSTRACT FROM AUTHOR]

Copyright of Proceedings of the International Congress on Process Engineering - Processing is the property of Union of Mechanical & Electrotechnical Engineers & Technicians of Serbia (SMEITS) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In accordance with the increase in consumer awareness of the negative consequences of pollution of the natural environment, many industries are adjusting their activities, striving for the placement of products and services that are environmentally acceptable and based on the postulates of sustainability. In order to reach consumers more easily, manufacturers in various industries are adapting elements of their brands to make them green as much as possible. The so-called „green wave” affects changes in the behaviour of producers in all sectors of the economy, including wine producers. Wine consumers around the world have different attitudes regarding green marketing activities. The aim of this paper is to gain insight into the attitudes and intentions of wine consumers in relation to the eco-friendly activities of wine producers in Bosnia and Herzegovina. [ABSTRACT FROM AUTHOR]

Paid promotions have become less significant for modern travelers due to the high risk involved in the decision-making process. Instead, noncommercial and limitless Internet recommendations (electronic word of mouth - eWOM) are considered as crucial sources of information. Therefore, the subject of this paper is the eWOM recommendation system, with a particular emphasis on travel websites. Over 30% of Internet users have rated products and/or services at least once through the network. However, very little is known about what influences travelers to share their experiences, beyond their concern for others and desire for enjoyment/positive self-enhancement. To analyze the influence of travel website complexity (presence of text, ease of use, and updated content) on consumer behavior, Pearson's Correlation test is used. The analysis results indicate that attitude toward the travel website has a positive effect on the consumers' willingness to write a recommendation. The main findings suggest how to effectively design engaging travel websites that can compete successfully in a highly competitive information environment. [ABSTRACT FROM AUTHOR]

In the context of sustainable materials and technologies, advanced visualization technologies like AR and VR have emerged and integrated in the Retail Jewelry Segment. Can the integration of sustainable immersive technologies in retail jewelry segment contribute to the future of sustainable business goals is to be explored. This research study examines the above study area of analyzing the role of sustainable AR/VR experience on customer perceptions in retail jewelry sector. This paper aims to explore if immersive technologies influences customer perceptions like brand associations and purchase behaviour leading to brand loyalty in the landscape of sustainable jewelry business. Based on a thorough literature review, conceptual framework and hypothesis were formulated to test the interactive, novel and vivid features of AR/VR immersive technologies. To validate this, relational study methodology was adopted, using judgmental sampling 227 customer surveys and insights from jewelry retailers who had adopted AR/VR technologies in their operations. Validated scales was used for collecting the data from customers. SEM analysis was administered to review the model in 2 different stages. Reliability and validity tests followed by various Fit Measures were computed to confirm the results. The results proved that customer perceptions were greatly influenced by AR/VR experiences. By exploring the implications of AR/VR experience in sustainable retail jewelry segment, this paper contributes significant recommendations and marketing strategies that cater to the evolving concept of sustainable materials and technologies. [ABSTRACT FROM AUTHOR]

With the advent of cloud computing, novel methods of system design have emerged. Cloud providers now offer computing power and storage as a service, allowing customers to outsource computations more extensively than ever before. As sensitive data migrates to the cloud, ensuring privacy and security becomes increasingly critical for users. Fully Homomorphic Encryption (FHE) presents a contemporary approach to address these concerns. As far as my knowledge extends, this appears to be the initial academic publication focused on FHE. The article employs not only to explore a systematic analysis of fully homomorphic encryption but also to assess its practical implementation feasibility with novel techniques. Various papers on FHE have been aimed at enhancing efficiency and reducing noise through innovative techniques. A novel algorithm has been introduced to enhance the security of data transfers. The final thematic modeling study of this paper ensures that all discussed articles center around cloud computing and FHE. [ABSTRACT FROM AUTHOR]

Nowadays Online purchase possesses a vital role in our day to day life. People started purchasing goods through online rather than offline. This paper reveals the impact of consumer perceptions and awareness of goods and services offered online and also helps to understand how it provides goods and services to its clients. E-Commerce is one of the wonderful technological advancement platform which has made our life very easy. It is also helping us to manage time, work life balance, stress, depression etc. Online platform is used by working people, home makers, children, organization etc without which we cannot think about our life. Let us discuss in this paper about consumer motivation behind online purchases with the help of the data collected and analyze the real situation faced during this current era. [ABSTRACT FROM AUTHOR]

With burgeoning technologies, comes novel ideas that could potentially boost businesses and solve existing problems in the contemporary world. Tremendous advantages of the hybrid realm of the Internet of Things and Machine Learning can be rightly exploited for large benefits. One instance of day-to-day activities is the necessity to wait in long queues at the billing counters in shopping malls, which could be tiresome. Also, any strategy that has been made to improve sales in shopping malls is futile. This paper, hence, proposes a system that attempts to improve customer convenience as well as aims to maximize sales. An IoT-based approach using ESP32 and RFID modules is adopted, combined with Data Mining techniques to achieve the motive. Also, this paper describes how the billing data is transferred over Wi-Fi to different devices, the transaction of data between ESP32 and Firebase, and methodologies adopted to improve sales by recommending products to customers based on transactional history by creating a user interface. [ABSTRACT FROM AUTHOR]

The continuous of purchasing online products, For the buy of any product, we must see the reviews of that product after that we purchase the products. Review places the main role in online purchasing the product. Mainly positive reviews make customers buy a product online, similarly, the negative reviews make confusion about whether the customer buys a product or not. The product seller wrote a fake review to satisfy the customer. Thus, identifying fake reviews is a faithful and ongoing research area. Identifying a fake review depends on key features of the review but also it depends on behave of the reviews. This paper proposes a Machine learning accession to the identification of fake reviews. In addition to the features eradication process of the reviews. This paper appeal to some features engineering techniques to essence various behave of the reviews. This paper equates the performance of some trail runs on a real dataset of online shopping reviews with and without features estimations of users' behavior. In both cases, we compare the performance of some classifiers: K-Nearest Neighbor (KNN), Navy Bayes, Logistic Regression, and Random Forest algorithm. [ABSTRACT FROM AUTHOR]

A food-related lifestyle (FRL) is a theory-driven approach proposed by Grunert et al. (1993) and Brunsø and Grunert (1995) that aims to discover how consumers use the attributes of a product to attain significant life values (Fang and Lee, 2009). It consists of 69 statements, each of which can be arranged according to 23 dimensions covering five different FRL domains, including ways of shopping, cooking methods, quality aspects, consumption situations, and purchasing motives. The FRL instrument has been used widely in Europe, the US, and China, providing insight into consumer motivation, food consumption, and purchases (Yeo et al., 2020). The instrument has been tested and validated in several countries, indicating great validity and reliability in international settings. It was also used for segmenting consumers (Montero-Vicente et al., 2019; Yeo et al., 2020). Still, the instrument works well in Western cultures, while it is less successful in other parts of the world (Grunert et al., 2011; Montero-Vicente et al., 2019). Consumer segments and their characteristics vary depending on the context. In marketing literature, young consumers, i.e., generation Z consumers, are often treated as a compact consumer group compared to other consumer generations (for instance: Wahyuningsih et al. 2022; Dorie and Loranger, 2020), but there is a scarcity of papers addressing sub-segments within young consumers, especially when it comes to their food-related lifestyles. Therefore, more research is needed to validate the concept in various contexts and population segments, particularly among young consumers who are expected to generate significant revenues in food retail in the next couple of years. To address the gap in the literature, our paper applies a food-related style instrument (Brunsø and Grunert, 1995) among young consumers in Croatia. It aims (1) to reveal the patterns of food-related lifestyles, (2) to determine consumer segments based on FRL factors, and (3) to elaborate these segments according to their socio-demographic characteristics (i.e., gender, household income, and type of household). Our paper relies on a survey based on the FLR scale questionnaire, conducted among university students at the University of Zagreb, Faculty of Economics and Business, since April 2021 in a couple of generations of students at various levels of study. The sample consists of 641 university students. Several statistical methods were used to analyze the data. Factor analysis with the principal component method was employed to identify FRL dimensions, hierarchical and non-hierarchical cluster analysis to identify groups of individuals with similar styles, and a chi-squared test to analyze the differences among the groups in their socio-demographic variables. The findings discovered 11 dimensions of food-related lifestyles that differ somewhat from the original FRL dimensions. Based on these dimensions, four groups of consumers were identified: (1) convenience-oriented individuals, (2) active individuals, (3) novelty seekers, and (4) family-oriented individuals. These groups differ significantly in gender, household monthly income, and type of household. Convenience-oriented consumers are the most interested in convenient cooking methods and prefer snacks over meals. This group comprises often males who live with their parents and have higher incomes. Active consumers are most interested in product information and prefer cooking with their families, security, taste, and food freshness. They are composed primarily of females. In this group, there are more married couples with moderate income. Novelty seekers like trying new foods, recipes, and unusual meals. They are the most independent among young consumers and have moderate incomes. Family-oriented individuals value the most family involvement in cooking. The findings can be helpful for researchers in marketing and retail management to understand the FRL concept and segments of consumers. The novel finding is that consumers within so-called “compact” consumer generations are not the same and, thus, different segments require different approaches in retail marketing and management. Findings are relevant for managers in food supply chains because they can help food producers and retail managers design their promotions and develop food assortments based on particular consumer preferences. Furthermore, findings can be helpful in markets where young people represent an important market segment for food products. Our study has a few limitations. The sample includes only young adult consumers in one market (Croatia). Thus, results can be valid only for this group of individuals in similar markets. Future research might examine FRL groups from the perspective of adopting new products and food purchasing behavior. Patterns of FRL and groups of young people can be compared across a region of Central and Eastern Europe or the European Union. [ABSTRACT FROM AUTHOR]

Becoming a provider of Product-Service Systems (PSS) is a promising but challenging way for companies to operate more sustainable and provide more innovative solutions to their customers. However, this also requires a transformation of the companies' current business model. In the literature, several generic approaches can be found to visualize business models. These are largely generic and vary in the number of proposed design categories. Although it is possible to represent PSS-driven business models with these generic approaches, it was found in a joint research project with SMEs that the special aspects of PSS-driven business models are not sufficiently represented. Especially in early phases, this can hinder the innovation process. For this reason, this paper presents a design approach for business model innovation with the help of PSS, which makes it possible to consider the specifics of PSS in business models in a more focused way. [ABSTRACT FROM AUTHOR]

An analysis presented in the paper reveals that most equipment requires a DC power supply (low voltage and low current) rather than an AC power supply, like computers and peripherals, audio-video players, food preparation. Moreover, there is the possibility that through minimal adaptations and other equipment they can operate in DC microgrids. A validation for one or another microgrid types, when the AC grid has priority, is based on an in-depth study. There are currently consumers (especially in the home appliance field) that can be used successfully in bothmicrogrids (AC and DC). This category of receivers includes AC electrical light sources, which study and analysis of compatibility in DC network, will be detailed in the paper. The research results conduct to the conclusion that most of the AC consumers used nowadays, are easy to use and adapt to a DC microgrid, like the residential low voltage electric network. Paper will focus only to a detailed analysis for one lightning source. [ABSTRACT FROM AUTHOR]

Customer profiling is one of the important aspects for retailers or service providers used in analyzing consumer characteristics and needs. To build a customer profile, various customer information can be used ranged from demographic information (such as age, gender, salary, address) to customer behavior (such as the frequency to visit shop and money spent). Due to the enormous amount of information available, it becomes inefficient to analyze it through descriptive analysis. Instead, data mining can be used to cluster and summarize the huge amount of information without much information loss. This paper discuss method of utilizing LRFMP (Length Recency Frequency Monetary Periodicity) model and K-means clustering in data mining techniques to perform customer profiling. Furthermore, this paper will describe the evaluation of this work which is based on Elbow method, Silhouette Index, Davies-Bouldin Index, and Calinski Harabasz test. The result suggested LRFMP model is a viable model in customer profiling when use together with K-means clustering technique despite some variable may had contributed less than another. [ABSTRACT FROM AUTHOR]

Sustainability is influencing the automotive industry. Car manufacturers are increasingly prioritizing sustainable materials. The production of these still pose environmental challenges. This paper addresses the trends related to sustainable car interiors. It emphasizes the importance of understanding how customers perceive these new materials. Seven in-depth interviews were conducted, followed by a survey with 106 participants to obtain generalized insights. The results will reduce the uncertainty regarding customer expectations for sustainable car interiors. [ABSTRACT FROM AUTHOR]

Using foresight methods such as scenarios, possible futures can be described and anticipated. Needs and requirements as well as product properties can be derived from that, which is necessary to plan successful products for future customers. Changes that occur in the future development can be identified with monitoring and the expected future can be adjusted. A consistent understanding of the use of monitoring for the product engineering process does not exist and is developed in this paper. Thereby, monitoring is considered in the context of validation and located in iPeM. [ABSTRACT FROM AUTHOR]

IoT has been developing, because of which the variety of customer demand for the layer of fog computing has similarly expanded. Fog Computing takes care of the actual time work environment and outputs are processed instantly by associated gadgets. The virtual machines (VMs) on the Fog Layer are becoming increasingly overloaded as customer demand for the Fog Layer has skyrocketed. A load balancing mechanism allows the load to be distributed equally across all VMs. Within the fog layer, the entire workload should be evenly and fairly distributed across multiple current VMs within the segment. So far, several load-balancing strategies have been initiated for Fog Computing Analysis. An empirical survey of current load-balancing techniques has been taken into consideration and a taxonomy is provided structurally. The paper also includes annual summaries and in-depth survey papers published in this field of load balancing from 2017 - 2022. In addition, this article also consists of fog computing constructs proposed to clarify the load balancing issue. In addition, we will discuss current problems and difficult situations that can be solved with destiny studies. The paper concludes by pointing out future directions. [ABSTRACT FROM AUTHOR]

The economic uncertainties due to Covid-19 pandemic has forced businesses to survive, maintain their long-term profitability and remain competitive through the unexpected market upsets. As businesses have to shut down, jobs are lost, people will suffer and economy will be shrinking. Thus, understanding the purchasing behavior of customer is a vital step not only in building but also in maintaining a business. Good customer management comes from good customer measurement. With the latest advent of customer analytics, businesses nowadays can thoroughly comprehend their consumers at all phases of the purchasing process, recognizing patterns in customer data, forecasting the actions that their customers will do, and then making decisions about how to enhance their business in order to attract new customers and retain existing ones. The objective of this paper is to perform customer profiling and customer segmentation of Starbucks Malaysia during the hit of Covid-19 pandemic in Malaysia. Dataset are collected during the second Conditional Movement Control Order (CMCO 2.0). Customer profiling tries to gain a deeper understanding of customers and describe their personalities types or personas, while customer segmentation is a powerful technique to understand the patterns that differentiate a customer. A customer segment is a grouping of customers that share certain characteristics. In this paper, k-means clustering algorithm is used to segment the customers of Starbucks Malaysia according to their income and spend data. From the clustering analysis, one can determine the optimal number of clusters and comprehend the underlying customer segments to identify the statistical patterns of Starbucks customers. This research will contribute both theoretically where this research can uplift the theoretical foundation of customer analytics and practically towards Starbucks Malaysia and other organization and marketing teams where they can understand their customers better and can increase their revenue with the improved marketing campaigns especially during this long-run Covid-19 crisis. [ABSTRACT FROM AUTHOR]

Freezer and refrigeration plants are among the highest consumers of electric energy because they must provide sufficient cooling capacity. At present, the technical standard for design, the European document for the technical approval of EOTA and the recommendations of refrigeration and logistics associations have to be applied to this area in the conditions of the Czech Republic. The recommendations focus on efficient energy consumption, targeting energy fuels, reducing CO2 emissions, which helps to suppress global warming as a result of climate change. The paper demonstrates the degree of energy savings by numerical modeling due to the shielding of solar radiation acting on the perimeter cladding by structural modification of the outer overhanging façade with a ventilated air layer. [ABSTRACT FROM AUTHOR]

Business competition in the service sector in Indonesia makes the queuing model very important. This paper aims to find the optimal queuing model at the XYZ counter area service. The average customer arrival time in the ongoing XYZ model simulation with only one entry is 34.1 seconds. With three queue lines and three cashiers each accommodated with ten samples, the duration of service for each cashier independently is 61.4 seconds, 53.2 seconds, and 68.4 seconds. The number of customers served is 4 out of 16. This fact shows that this queue is not adequate for optimal service. The researchers made two simulation models for counter row reduction in this study. First, the researcher made two entries, four queue lines, and four counters. The number of customers served is 24 out of 67, which makes the first model has an effectiveness of 35.82%, which is more advanced than the effectiveness of the current model. Second, the researcher makes one entry, one queue line1, and one counter1. The number of customers served was 5 out of 16, making the alternative model 31.25% effective, which is also ahead of the current model. [ABSTRACT FROM AUTHOR]

Design of water distribution network (WDN) for intermittent supply system is one of the challenging tasks. Its design on current and futuristic need shall be planned properly so that proper phasing and upgrading can be done effectively once it reaches at different states. The main problem faced by WDN is the pressure deficient condition. Whenever more flow is drawn at certain user nodes due to rapid urbanization and increase in population in certain packet of the region, pressure deficiency state. It is regular situation that certain consumers enjoy uninterrupted water distribution with sufficient pressure head and whereas, users located at remotely from supplying source faces with deficient supply due to deficit availability pressure head. The pressure at ferrule point in the WDN is more important to provide adequate service pressure and it is hardly met owing head loss that occurs from the source to sink. Due to these kinds of reason, meeting supply equitably is found to be challenging. This paper normalises the street and city pipelines for equitable water distribution using hydraulic simulation. The case study is based out of Kailashnagar, Trichippalli in Tamil Nadu considering its population and phasing construction barriers. Several analysis for satisfying the criteria was made with many methods, and all of them have been evaluated to finally adopt the best cost - effective option serving the needs of population growth. The same network was used and assessed to determine the size of pipeline needed for the building pipeline network. [ABSTRACT FROM AUTHOR]

When viewing a product for the first time, a consumer's aesthetic perception is based on their knowledge of other products, artefacts, and concepts. These mental images function as visual references for consumers and affect the processing fluency of the new product. Designers frequently use visual references as inspiration during the research stage of the design process. It has been documented, however, that there is a gap between designer intent and consumer response; Consumers do not always realize the intent of designers nor draw on the same visual references when perceiving a product, which can reduce their processing fluency of new products. Visual references differ from one consumer to the other which make them difficult to study. In this paper, we argue for a new way of studying visual references: by analyzing the cognitive process that occurs when consumers view a new product and recognize aspects of that product that are similar to visual references in their memory. We present a framework of three approaches for recognizing this similarity and implications for design practice. [ABSTRACT FROM AUTHOR]

In the digitalization of the present world, customer-based E-services have made a lot of progress because of thefusion of the E-commerce sector with the machine learning paradigm. It presents an appropriate, flexible and easy-to-use environment for the customers to purchase the products and give them a variety of products through the Internet. Today's industrial scenario moves toward the client-centric market. So, this market requires the effective partitioning of customers using influential effective elements. This paper presents a detailed study of customer behavioral and segmentation models for E-satisfaction using K-Means, modified K-means, and other variations of K-based clustering techniques. It provides the comparison of the statistical and analytical results of various existing models along with the consideration of their data attributes and effective elements. Further, it provides suggestions and extensions to improve their results in the E-market. It also signifies the need of K-prototype algorithm. Therefore, such a review provides an analysis of the E-Satisfaction, and of the behavior and loyalty of the customers in the ML-based paradigm. [ABSTRACT FROM AUTHOR]

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This paper is focused on the overview of the organizational factors affecting Lean marketing readiness in the retail sector in Sri Lanka. Retail businesses are one of the fast-growing sectors in Sri Lanka. However, retails have to compete with each other for the small consumer base inside the country. Those retailers should be able to attract their consumers and communicate with them using marketing. This study is conducted as a systematic literature review by reviewing 34 papers using the PRISMA framework. This study has identified several main organizational factors affecting lean marketing readiness: Management and leadership; Lean tools, techniques, and knowledge about Lean concepts; availability of organizational resources; organizational culture and business processes; employees' involvement and skills; communication management. This systematic review is the first attempt to overview the organizational readiness for Lean marketing readiness in the retail businesses area. [ABSTRACT FROM AUTHOR]

This paper summarizes the perspectives of health and wellness tourism consumers, to better understand the factors that influence this tourism product. A quantitative approach was adopted to collect primary data through the application of an online survey to effective and potential health and wellness tourism consumers between January and April 2021. Results show that growing number of consumers tend to value health and wellness tourism as a holistic experience, in which not only products specifically related to health and wellness treatments are of particular importance, but also activities related to leisure, recreation and culture. This paper provides a basis of research and analysis for global wellness and tourism industry stakeholders. The aim is to help the industry understand consumer behaviour and preferences in the traveller's process of choosing a destination for a wellness vacation. This is achieved by predicting wellness tourism trends and developments, by acknowledging the gaps in the research available for understanding wellness tourism and reflecting the experience economy perspective in the sector. [ABSTRACT FROM AUTHOR]

The study aims to build an efficient feedback system for automated and unmanned restaurants using customers facial expressions by training the model with six different expressions and produce accurate results. The proposed system uses an improved support vector machine for recognizing various expressions of human face in the unmanned restaurants based on a gradient boosting approach. FER2013 dataset has been used for the implementation. This study consists of two groups and the sample size for each group is 392. This research study adapts a novel gradient boosting with kernel trick approach for efficient classification. It is observed that the proposed system obtained 82.14% accuracy while comparing with the existing system which has only 63.88% of accuracy. The result proves that the improved support vector machine with a gradient boosting approach for the feedback system of unmanned and automated restaurants obtained better accuracy than the existing system. This feedback system can also be used as a resort feedback system in order to improve the customer experience. [ABSTRACT FROM AUTHOR]

Nowadays, the competitors for car retails are increasing very rapidly and every retailer should know their customers' expectations and try to reach them. This paper represents a customer segmentation model which helps them to group the customers with the same market characteristics. Materials and MethodsThe study contains 2 groups i.e, the K Means clustering model is developed in the first group and Regularized Logistic Regression model, a supervised machine learning algorithm is developed in the second group. Each group has a sample size of 200 and the study parameters include alpha value 0.05, beta value 0.2, and the power value 0.8. The accuracies of each model are compared with others for different sample sizes. Result: This paper is an attempt to improve the accuracy of customer segmentation using the Regularized Logistic Regression(RLR), a supervised predictive machine learning algorithm. The L2 or Ridge Regularization avoids the overfitting of the data. The proposed model has an improved accuracy of 87.5 % with p < 0.05 in segmenting customers than the existing model of 85 %. It helps the car retail entrepreneurship be more reliable and robust. The outcomes of the proposed model are compared with the K Means Clustering algorithm and the proposed model confirms to have higher accuracy than the K Means Clustering algorithm. [ABSTRACT FROM AUTHOR]

It’s inevitable that electric vehicles are going to shape the future of the automobile industry. This paper focuses on establishing a vital fact about the introduction and implementation of electric vehicles in India. The researcher has discussed the scope, practicality, & foreseeable period of enforcement of electric vehicles in India. An extant literature review was done to analyse current study trends on the topic. Primary data has been collected from an establishment called “The Young Business Leader Forum”, a platform for future generation entrepreneurs indulged in the automotive sector, created in association with Automotive Component Manufacturers Association (ACMA). The paper further highlights & analyses the interpretations & viewpoints of entrepreneurs with respect to the time period for introduction, current players in the market, future market leaders & important factors consumer seek while buying an electric vehicle. This will help in understanding as to how & by when one should strategise with the future dynamics in the environment and what they should look out for. It is essential for researchers to estimate and understand such a transition in the industry in the future so as to be able to cope with the changes effectively. The results from the study can be used to comprehend and compare the current situation of electric vehicles along with an estimated & predicted culture & mobility of electric vehicles in India. [ABSTRACT FROM AUTHOR]

Coffee shops are currently developing and becoming a lifestyle for many people in Indonesia, especially the city of Depok. The boom of customers in coffee shops has caused several machines to be overused and damaged. In this paper, we take 30 coffee shop samples to be surveyed in Depok to find out how to plan machine maintenance for each coffee shop and find an ideal way for preventive maintenance. This research paper aims to study preventive maintenance plans and analyze preventive maintenance carried out by each coffee shop by statistical analysis using F-Test in IBM SPSS. The data used descriptive statistical analysis and then continued with testing the validity and reliability of the data. Before being tested using multiple linear regression analysis to prove the hypothesis, the classical assumption test was first carried out. [ABSTRACT FROM AUTHOR]

Product Service Systems are considered a new, circular business model that could help businesses be sustainable while maintaining economic growth at the same time. Consumer innovativeness can predict and influence acceptance of such novel business models. However, differences in innovativeness can vary across countries and should be considered in research. This study aims to examine differences and influence of consumer innovativeness on consumer acceptance of Product Services Systems based on data collected from Czech Republic, Sweden and Hungary. For the analysis pay-perwash was chosen, as washing machines are one of the most used everyday products. This paper takes a descriptive and quantitative approach while using regression as a data analysis method. The findings enrich current scarce knowledge of differences and influence of consumer innovativeness on consumer acceptance of Product Service Systems, especially considering that Central- and Eastern European countries are underrepresented in the literature. For the managerial contribution, the study offers insights for more efficient consumer segmentation and targeting for introduction of pay-perwash services. [ABSTRACT FROM AUTHOR]

When facing unprecedented environmental changes, a company's survival strongly depends on its ability to cope with challenges by making timely and adequate changes in its business. This paper presents the results of a study on Bulgarian textile and apparel companies and the changes they have implemented in their activity in the period 2020 - 2021 while facing the COVID-19 crisis. Based on the understanding that making changes requires both the ability to sense the need for change and the ability to implement said change, this paper aims to find empirical evidence that companies which perform above average are those which not only sense the changes they need to make to their products in order to address customer needs, but also make changes in their internal business process in order to implement those. Additionally, this paper seeks empirical evidence for the presence of those organizational attributes in successful organizations which are seen in literature as enablers of organizational agility. The conclusions are expected to be useful by adding empirical evidence for the connection between organizational performance and agility capabilities, as well as for the role of some organizational attributes as enablers of agility. [ABSTRACT FROM AUTHOR]

In the machine learning era, aspect-based sentiment analysis is a very popular idea that is still in the research realm. The main objective of this paper is to derive new pattern-based rules for Aspect Extraction. This focuses on the Explicit aspects where the aspect is precisely defined, unlike the previously researched papers on Aspect Extraction, this model does not limit itself to the noun/noun phrases but also focuses on the other words like verbs in a review. Newly extracted pattern rules for aspect extraction would be proved beneficial in terms of sentiment analysis of online customers. [ABSTRACT FROM AUTHOR]

Budget-conscious tourists are travellers electing to plan their vacations by taking advantage of pricing variability to minimize the total cost of their desired multi-city vacation. This paper presents the formulation and analysis of a timediscretized linear integer programming (LIP) model to optimize total travel costs for travellers vacationing between major European cities by considering dynamic flight costs and accommodation expenses. The proposed timediscretized network flow model presented is an extension of classical Shortest-Route-Problems (SRP) and is solved using Excel's SIMPLEX LP algorithm. Flight data collected from the online travel agency Kiwi.com between May 1st, 2022, and May 30th was found to show significant daily price fluctuation, whereas accommodation prices collected from Airbnb.com between May 1st, 2023, and May 13th, 2023, remained stable. This paper includes the model formulation, assumptions, and cost analysis of varying travel instances by rotating the origin city and altering the stay duration at each destination. Three solutions, the generous, greedy, and cost-minimized solutions, were calculated for each travel trip instance. By optimizing the route, the cost can be reduced by upwards of 20.3% and 6.7% relative to the generous and greedy solutions. The model evaluated the impact of varying staying durations on the optimal travel order and was found to be very robust in terms of stay durations such that the optimized cost remained constant. The results of this paper have implications for the global travel industry by lowering the barrier of entry for budget-friendly consumers. [ABSTRACT FROM AUTHOR]

The article focuses on conceptualizing virtual volunteering (VV) and its unique characteristics compared to traditional in-person volunteering. Topics include the defining dimensions and task attributes of VV; the perceived benefits of virtual versus physical volunteering; the impact of technology on volunteer engagement; and study identifies VV as a distinct form of volunteering characterized by its reliance on technology and absence of physical interactions.

Geographical indication of origin, which identifies a certain product as originating from the territory of a certain country, region or locality from that territory, is also much more than that. By acquiring it, apart from announcing where it comes from, it is made known and publicly announced that the product has a certain quality, which potential users and consumers expect. This would represent one dimension of the geographical indication of origin. Another dimension would certainly be the promotion of the geographical area that has been marked, through different types of tourism - rural, event, spa, etc. The authors of this paper will try to find a connection between the geographical indication of origin of a certain product and the development of tourism in a given area, using the example and available statistical data on Futog's fresh and sour cabbage, which received its geographical indication of origin by the Decision of the Intellectual Property Office in May 2008. [ABSTRACT FROM AUTHOR]

Within the new era of digitalization, software development and personalization projects play a major role for the IT & Telecommunication players. They also come with a range of associated risks like the risk of not being able to deliver on time, on budget or the needed scope. It is thought that having the clients directly involved in the development and personalization process comes with a range of benefits that help lower the project's overall risk. In order to demonstrate the added value of supplier-client collaboration in such a context, a research has been put in place. During the four months' research period in 2017, one hundred responses were gathered and the results of the study are presented in this paper. The results of the paper will be displayed from two main different angles that consist in the business users' perception of the value added resulted from these types of collaborations along with the technical user's perception on the same topic. The paper will end by focusing also on the type of knowledge that a client can bring in a software personalization project. [ABSTRACT FROM AUTHOR]

The application of artificial intelligence in retail is an inevitable trend that originated from developed markets and expanded to emerging ones as well. Modern retail is using various information technology systems based on artificial intelligence to improve its business performance and achieve a competitive advantage. The paper outlines the theoretical aspects of the application of artificial intelligence in retail and empirically studies the acceptance among consumers in Croatia. The aim of the paper is to indicate benefits and uncertainties associated with application of artificial intelligence in retail and to study how consumers react to AI technology at point of sale. Results reveal that consumers show moderate to high understanding of artificial intelligence in retail, assess their own acceptance of it as moderate and find customizing feature as a most valuable merit. Findings offer great practical implications as they can be used in digital marketing and indicate need for further education of consumers on benefits of application of artificial intelligence in retail. [ABSTRACT FROM AUTHOR]