Market Research Analysis Research Articles

Application and Impact of Marketing Mechanisms in the Perspective of New Public Management

This paper explores the application and impact of marketing mechanisms within the framework of New Public Management (NPM). It begins by outlining the fundamental concepts of NPM and its differences from traditional public management, highlighting its significance in adapting to the era of globalization and knowledge economy. The paper then analyzes the specific application of marketing mechanisms in China's public sector, particularly in the promotion and optimization of e-government service platforms, demonstrating how market research and data analysis enhance the quality and efficiency of public services. Finally, the paper summarizes the value created by marketing mechanisms for the public sector and emphasizes the necessity of continuous optimization in practice to balance efficiency with equity, and market mechanisms with public interest.

Marketing Strategy Development in Entrepreneurship in the Creative Economy Sector, Tourism Sub Sector

To overcome the challenges in the tourism sector during the COVID-19 pandemic and restore the national economy, a strategy is needed to be able to survive and recover. One strategy that can be done is to innovate in marketing, find new markets, and guarantee security from the threat of COVID-19. This will make tourists interested in visiting and continue to comply with health protocols so as not to be exposed to COVID-19. In addition, it is hoped that tourism in Indonesia can recover after experiencing a downturn due to the COVID-19 pandemic. This research aims to analyze marketing strategy development in entrepreneurship in the creative economy sector, tourism sub sector. This type of research uses qualitative research. The object of the research is the creative economy sector, tourism sub sector in Indonesia. Data collection for research purposes uses secondary data. Data analysis in this study uses qualitative data analysis. The results of the study indicate that the preparation of marketing strategies in entrepreneurship in the creative economy sector, tourism sub sector aims to obtain, maintain, and increase tourist visits. The strategy consists of environmental analysis, marketing research analysis, and positioning analysis.

Conceptual Design of an Unmanned Electrical Amphibious Vehicle for Ocean and Land Surveillance

Unmanned vehicles (UVs) have become increasingly important in various scenarios of civil and military operations. The present work aims at the conceptual design of a modular Amphibious Unmanned Ground Vehicle (A-UGV) that can be easily adapted for different types of land and/or water missions with low monetary cost (EUR < 5 k, without sensors). Basing the design on the needs highlighted in the 2021 review of the Strategic Directive of the Portuguese Navy, the necessary specifications and requirements are established for two mission scenarios. Then, a market research analysis focused on vehicles currently available and their technological advances is conducted to identify existing UV solutions and respective characteristics/capabilities of interest to the current work. To study and define the geometry of the hull and the configuration of the A-UGV itself, preliminary computational structural and fluid analyses are carried out to ensure it complies with the specifications initially established. As a result, one obtains a fully electric vehicle with approximate dimensions of 1050 × 670 × 450 mm (length–width–height), enabled with 6 × 6 traction capable of reaching 20 km/h on land, which possesses amphibious capabilities of independent propulsion in water up to 8 kts and an estimated autonomy of over 60 min.

Analysis the Gaps in Adopting Quality System as per the National Standard of Accreditation on Territory Care Hospital with Reference to NABH Standards

This research paper delves into the pivotal role of product management and market research analysis in the context of pharmaceutical companies. It explores how these strategic tools contribute to business development amidst the intricate landscape of the pharmaceutical industry, characterized by rapid scientific advancements, evolving market dynamics, and stringent regulatory requirements. The paper emphasizes the evolution of product management within the pharmaceutical sector, highlighting its transition from a focus on research and development to encompassing comprehensive lifecycle management and commercialization strategies. Through a review of literature and data analysis, the paper examines various facets such as patientcentric innovation, regulatory compliance, digital transformation, competitive landscape analysis, and cross-functional collaboration. The study aims to shed light on the significance of integrating product management and market research analysis for driving sustainable business growth, enhancing competitiveness, and delivering impactful healthcare solutions in pharmaceutical companies

A Systematic Literature Review of Trends in Digital Marketing Research in Romania

Abstract In the contemporary world, the significance of technology has become increasingly paramount. Hence, we are living in times in which the theme of digitalization is a transformative force, reshaping our daily lives and fundamentally altering the way we interact, work, and perceive the world around us. The paper aims to conduct a bibliometric analysis of digital marketing research in Romania. A total of 37 studies were found and systematized using inclusion and exclusion criteria. The papers were selected only if they featured research on digital marketing in the Romanian market. Using this search strategy, a literature review was conducted based on papers extracted from the Web of Science database. As a result, 16 papers were evaluated. Although the analyzed articles highlight quite a variety of things, the papers emphasize that digital marketing is an emerging subject in the Romanian market. This paper adds to the existing body of knowledge that digital marketing can be viewed from three perspectives: the impact of digital marketing strategies on consumer behavior in the technology era, exploring the nexus of digital marketing and social media: consumer engagement, trends, and impact, and digital marketing transformations across industries: trends, challenges, and opportunities.

Development of an International Qualification Framework for the Strength and Conditioning Profession: International Universities Strength and Conditioning Association Position Statement

In the profession of strength and conditioning (S&C), there is a need for a standardised, comprehensive framework that can allow for the alignment of international certifications, qualifications, and standards. This need stems from the lack of clarity surrounding the awarding levels of different governing bodies and organisations worldwide, as well as the increased connectedness of international sport and physical activity. Central to such a framework is understanding the current issues affecting S&C coaches,1 current professional standards and guidelines,2 and remuneration structures.3,4 As the sole dedicated international accreditation body, the International Universities Strength and Conditioning Association (IUSCA)5 carried out market research analysis and stakeholder engagement with regional and international educational authorities (Ofqual, European Commission, UNESCO, USDE, CHEA, TEQSA, ASQA) to develop a global framework for the rating and awarding of S&C courses, certifications, and qualifications.

The Role of Product Management and Market Research Analysis for Business Development in Selected Pharmaceutical Companies

This research paper delves into the pivotal role of product management and market research analysis in the context of pharmaceutical companies. It explores how these strategic tools contribute to business development amidst the intricate landscape of the pharmaceutical industry, characterized by rapid scientific advancements, evolving market dynamics, and stringent regulatory requirements. The paper emphasizes the evolution of product management within the pharmaceutical sector, highlighting its transition from a focus on research and development to encompassing comprehensive lifecycle management and commercialization strategies. Through a review of literature and data analysis, the paper examines various facets such as patient-centric innovation, regulatory compliance, digital transformation, competitive landscape analysis, and cross-functional collaboration. The study aims to shed light on the significance of integrating product management and market research analysis for driving sustainable business growth, enhancing competitiveness, and delivering impactful healthcare solutions in pharmaceutical companies.

Market Research and SWOT Analysis for Fibers Composite Materials Usage in the Vehicular Components Supply Chain

ABSTRACT Sustainability has become a global priority in recent years. The performance of companies in the market is directly influenced by their actions and the way they relate to consumers, who are increasingly looking for less environmentally aggressive products. The concept of ESG encompasses this concern with climate and environmental factors, while at the same time looking at the feasibility and operationalization of new practices. This is especially true in manufacturing sectors, such as the automotive sector, which is the subject of this study. Given the scarcity of information on who is involved in the production chain of automotive components and the possibility of production from more sustainable materials (such as the use of natural fibers), this work seeks to elucidate the gaps and opportunities for a new conception of automotive components, specifically in Brazil. Evaluating political, economic, social, technological, environmental, and legal aspects, and summarizing the data in a SWOT matrix, it identifies that the Brazilian automotive components production chain, despite its low technological level to absorb innovations, has opportunities for gains in technology development, alignment with global sustainable practices, increased competitiveness worldwide, and market positioning.

Public Relations Communication Strategies in Building Consumer Branding: Analysis of Unilever Company


 
 
 
 This article examines the Public Relations (PR) communication strategies employed by Unilever in building and maintaining a strong consumer branding. The study aims to understand how Unilever integrates PR communication strategies and adapts to the digital and social media era to create positive relationships with consumers. The research follows a qualitative approach, utilizing data collection techniques such as market research and consumer trend analysis and utilized a systematic Literature Review (SLR) method. The analysis reveals that Unilever emphasizes transparency, honesty, and consistency in their brand messages and values. They actively engage with consumers through social and environmental initiatives, creating a responsible and caring brand image. The results demonstrate that Unilever's PR strategies have successfully built a strong consumer branding and generated sustainable customer loyalty. The findings have implications for companies seeking to establish a positive and sustainable brand image in a competitive global market.
 
 
 

ARIF: Autonomous Recognition in the Field Enhancing National Security with Computer Vision-Based Facial Recognition

Through a novel research approach that employs a mix of Convolutional Neural architectures & Siamese Neural Nets, we propose a viable mechanism that focuses on leveraging these groundbreaking advancements, through the utilization of deep learning algorithms we were able to effectively & accurately identify and authenticate individuals based on unique facial features derived from machine learnt embeddings. In The ARIF Project we implement the proposed architecture models through utilization of developer friendly modules like the python facial recognition library, the OpenCV framework & Jupiter Notebooks, performing the necessary product development, market research and product analysis throughout the development process, finally deliver a refined & minimalistic solution that not only fills market gaps but also serves as a solid foundation for rapid adoption & deployment.

A Study on Exclusive Brand’s Marketing Optimization

This research walk-through the various methods used by exclusive and upscaled organizations that minimized its marketing Champaign and budgeting. Generally, posh products and service are not marketed through Integrated channels that are commonly available. As these companies differentiate themselves through unique innovative features they opt for specific single streamed path for marketing that directly reach-out its targeted customer group than spending on popularity promotions. In further discussions exclusive brand is categorized into known and Un-known, • Known Brands: Posh and exclusive brands that has a brand image among common customer base and spend on brand awareness and popularity promotion, such as Apple and Tesla. • Unknown Brands: Completely exclusive service or product which does not focus on brand awareness and also ensure they do not exist in common market, but strategically sustain stronger among its targeted customer segment. Study includes a market research analysis about the brand awareness and customer’s perceived knowledge about exclusive brands along their products and service that facilitate for its premium pricing.

Enhancing Sentiment Analysis Accuracy by Optimizing Hyperparameters of SVM and Logistic Regression Models

The Analysis of Sentiments expressed on Twitter is a widely practiced application of Natural Language Processing (NLP) and Artificial Intelligence (AI). This process involves examining tweets to determine the emotional tone conveyed within the message. AI-based approaches are employed in Twitter sentiment analysis, typically following these steps: Data Collection, Data Preprocessing, and Sentiment Analysis, where AI techniques like Support Vector Machines (SVM) and Logistic Regression are utilized to categorize tweets into positive, negative, or neutral sentiments. Twitter data is a valuable source of information, serving diverse purposes such as real-time updates, user feedback, brand monitoring, market research, digital marketing, and political analysis. The Twitter API (Application Programming Interface) provides developers with tools and functionalities to access and interact with Twitter data, including tweets, user profiles, and timelines, enabling a wide range of applications and services. However, Twitter sentiment analysis presents challenges such as handling sarcasm, irony, colloquial language, and coping with the sheer volume and rapid flow of Twitter data. Nevertheless, with effective preprocessing techniques and AI methods, Twitter sentiment analysis can yield valuable insights into public opinion on various topics.

Prospects for the development of the restaurant industry in hotel-restaurant complexes

After Covid 19, hazards appeared for the development of the hotel and restaurant business. Some of the skilled personnel left this business and headed for more sustainable industries or abroad. Therefore, the aim of the work is to study the main factors affecting the survival and prospects for the development of the restaurant business in the hotel-restaurant complexes in Bulgaria. The main motivations of consumers for the future development of modern restaurants in the country aimed at increasing customer satisfaction have been studied. The research was conducted through qualitative and quantitative marketing research and SWOT analysis of available high-end hotels and dining and entertainment establishments in Bulgaria. Mathematical and statistical models were used to process the data of the respondents for each of the questions. The results are presented graphically. A comparative characterization of six hotel-restaurant chains in Bulgaria was made in terms of categorization, comfort, amenities and quality of service, and way of eating in the restaurants. The positive sides and their shortcomings and prospects for development in the current economic situation are reflected, and the consequences of the Covid 19 crisis are also taken into account.

A Study on Digital Service Innovation Factors Influencing Organization Performance: Ajman Police Department in UAE

The study presented an analysis of the influence of four digital services innovation groups of factors on organizational performance. It identified 20 digital services innovation factors, which were categorized into four groups namely participation, inter-organizational collaboration, reflexivity, and responsiveness. The study focused on the Ajman Police Department in the United Arab Emirates and collected data through a structured questionnaire survey using a purposeful random sampling techniqueamong the employees ofthe department that involved 368 completed responsesfrom the employees. Statistical analysis was conducted using SPSS software. The study found that the five highest ranked factors by the respondents, which significantly impact organizationalperformance, are PP1 (Customer Feedback and Surveys), OC1 (Partnership with Complementary Service Providers), RF1 (Ethical Evaluation of Service Offerings and Practices), PP2 (Employee Brainstorming Sessions), and RS3 (Ongoing Market Research and Competitor Analysis). Additionally, the study established a mathematical model to predict organizational performance based on the four variables: participation, inter-organizational collaboration, reflexivity, and responsiveness. Furthermore, the study revealed that all five groups of factors, including organizational performancefactors, are significantly correlated. This research contributes to the understanding of the impact of digital services innovation on organizational performance, shedding light on the specific factors that play a crucial role in driving organizational success in the digital era. The findings provide valuable insights for organizations seeking to leverage digital services innovation to enhance their performance and competitiveness.

Generative AI: A master or servant of market research analysis?

This paper explores generative AI's potential impact on the analytics element of the market research process, examining whether AI is destined to become an analysis master (which reduces humans to a minor role), or whether it will play the role of a faithful, trusted and tireless servant to human researchers. Version 4.0 of ChatGPT was used to conduct a series of tasks ranging from the analysis of desk research to primary research qualitative transcripts, quantitative survey open-ended comments and numerical data. The paper concludes that the hype around generative AI is indeed justified. In its current state of evolution, ChatGPT is an extraordinarily efficient extractor, organiser, processor and summariser of qualitative, quantitative and secondary research data. However, its capability is more akin to that of a competent junior consultant; for projects which require a greater experience and understanding of the human condition (empathy, intuition, creative and abstract thinking), humans remain as, if not more, important than ever in helping brands to remain relevant and grow in an increasingly fast-moving and complex world. The paper concludes that a generative AI like ChatGPT 4.0 is an extremely smart, tireless, diligent collaborator which frees (or perhaps forces) human researchers to up their game so they can apply their uniquely human skills and value to the research process.

CONDITION ANALYSIS AND FORECASTING IN THE FASHION INDUSTRY: A COMPREHENSIVE STUDY

Condition analysis and forecasting play a crucial role in the fashion industry, enabling businesses to make informed decisions regarding product development, inventory management, and market positioning. This comprehensive study aims to analyze the current condition of the fashion industry and develop forecasting models to anticipate future trends. Through data collection, market research, and statistical analysis, key factors influencing fashion trends, consumer preferences, and market dynamics are identified. Various forecasting methods, including trend analysis, predictive modeling, and data mining techniques, are employed to generate accurate forecasts for product demand, market growth, and emerging fashion trends. The findings provide valuable insights for fashion businesses to stay competitive, optimize their operations, and meet the evolving demands of the market.

Utilisation of Social Media in Market Research and Business Decision Analysis

In recent years, social media has experienced significant growth and become a very popular platform for individuals and companies. Social media such as Facebook, Twitter, Instagram, and LinkedIn have become important places for people to interact, share information, and express their opinions. This study aims to conduct a review of current literature on the utilisation of social media in market research and business decision analysis. The focus of this study is primarily qualitative. Methods for gathering data include paying close attention to detail while viewing and recording data, and then using analytical techniques such as data reduction, visualisation, and inference to draw conclusions. The study concluded that utilising social media in market research and business decision analysis can provide significant benefits for companies in understanding consumers, identifying market trends, and making smarter business decisions. With direct access to real-time data and user insights, companies can unearth valuable information about their consumers' preferences, behaviours, and needs.

Tweet Sentiment & Emotion Analysis

Abstract: Tweet Sentiment & Emotion Analysis using Bi-LSTM in RNN. Twitter has developed into a useful medium for sharing ideas, attitudes, and feelings. Applications like opinion mining, market research, and social trend analysis all depend on the sentiment and emotion of tweets. The Bi-LSTM architecture in RNN (Recurrent Neural Networks) is used in this study to present an advanced method for sentiment and emotion analysis on Twitter. By utilising machine learning techniques, the objective is to increase the precision and efficacy of mood and emotion analysis. The study emphasises both conventional text analysis and real-time data analysis. Organisations and governmental bodies may continuously monitor sentiment and emotional patterns on Twitter thanks to real-time analysis, which enables them to react quickly to emerging problems or crises. In a typical text analysis, historical tweet data is examined to learn more about user viewpoints, emotional patterns, and sentiment distributions. The Bi-LSTM architecture is used because it can effectively capture the context and sequential dependencies found in tweets. To ensure consistent analysis, the system gathers real-time tweets and conducts the preprocessing stages. Monitoring sentiment changes, emotional responses, and new trends on Twitter are all made possible by this study. The goal of the research is to improve the precision and efficacy of sentiment and emotion analysis on Twitter by utilising machine learning techniques, real-time data analysis, and standard text analysis. The findings and conclusions will aid in understanding public mood and feelings in the digital age.

(301) Evidenced-Based Analysis of the Top 50 Testosterone Booster Supplements on Amazon Marketplace

Abstract Introduction As the population ages, the prevalence of age-related hypogonadism is expected to rise. Demand for testosterone replacement therapy (TRT) has increased, as evidenced by revenue from T prescriptions in the world increasing from $150 million USD in 2000 to $1.8 billion in 2011. A market research analysis shows the market for T was 10.9 billion USD in 2019. The NHIS survey in 2012 revealed that consumers in the United States spend annually $30.2 billion on dietary supplements of which include T supplements. Dietary supplements have gained in popularity, as they are more accessible since the advent of online marketplaces and relaxed testing protocols for safety and effectiveness. Of the online marketplaces available to purchase supplements, Amazon Marketplace has the majority share of online sales at 41%, with the next largest retailer occupying only 6% of online sales. The aim of our study was to determine and evaluate the evidence behind the top 50 dietary T supplements (ranked in terms of sales) sold on Amazon Marketplace. Objective 1. Determine the product characteristics and claims made by the Top 50 T supplements sold on Amazon Marketplace. 2. Determine the cost to the consumer and customer satisfaction with these products. Methods The top 50 T supplements were determined by visiting the Amazon page, “Best Sellers in Sports Nutrition T Boosters,” which lists the top products based on sales and revenue. Active ingredients, number of active ingredients, 30-day costs, 5-star ratings, refunds, and claims of these products were documented. Ingredients present in a minimum of 50% of products were analyzed. Results A total of 50 supplements were analyzed. The three most common claims were “boosts/supports T” (46/50), “increases muscle mass” (46/50), and “increases energy” (45/50). The average number of claims a product made was 4. The average 30-day cost of a product was $25.95, with cost ranging from $6.66 to $84.99. The average customer satisfaction rating of these products was 4.23 (1-5), ranging from 3.4 to 4.7. Forty-seven out of 50 products did not offer a refund. A total of 129 unique ingredients were identified with 57% of the ingredients being unique to one product. Only Tongkat Ali root extract (Eurycoma Longifolia, EL) was used in a minimum of 50% of the supplements analyzed (59%) and thus further analyzed for efficacy and safety. Two randomized, double-blinded, placebo-controlled trials examined the efficacy of EL. One of the trials only showed improvement in total T levels when EL was used concurrently with exercise. The second trial, which examined 32 patients either receiving placebo or EL, showed an increase of T levels in the EL group. No clinical trial has examined the safety profile of EL in patients. Conclusions There is large heterogeneity in the composition of T supplements sold on Amazon Marketplace, and these products can present a significant 30-day cost to patients despite having no strong evidence regarding efficacy and more importantly safety. Further research and trials are needed to examine the most common ingredients needed in these supplements. Disclosure No

Monetising User Participation, Content and Expertise: Sources of Income for Indonesia’s Digital News Media

The global news media industry is still looking for a sustainable business model. The digitalisation of the media has forced the global press industry to seek compensation for lost revenue traditionally derived from advertising. A similar phenomenon is also occurring in a Global South country, Indonesia. With many social media users and thousands of startups, the opportunity to benefit comes from two channels: monetising user participation and content. What is the current position of conglomerate and digitally native news media on the two options? How are websites and social media used by both media to support these two sources of income? The research applied two methods, website content analysis and social media analysis, to see revenue channels, web functions, user participation on the web, and social media functions. In addition, we interviewed eight informants from eight media. This research finds that digital news media conglomerates and Indonesian startups earn profits through similar channels, such as monetising user participation and content and their expertise. However, slightly different from established digital media, digital native media companies expand their revenue stream by monetising their expertise, for example, by offering market research and data analysis. Digital news media with a niche market of readers will most likely offer their expertise. Keywords: Media business model, digital news media, paywall, user participation, user-generated content.