Market Research Research Articles

The Australian Frailty Network: Development of a consumer-focussed national response to frailty.

Frailty is an important concept in the care of older adults. Over the past two decades, significant advances have been made in measuring frailty. While it is now well-recognised that frailty status is an important determinant of outcomes from medical illnesses or surgical interventions, frailty measurement is not currently routinely integrated into clinical practice. In the community setting, it is uncommon for general practitioners to deliver frailty-optimised care. In hospitals, there is substantial variability in how people living with frailty are managed. This variability is notable between and even within disciplines. Furthermore, gains from understanding frailty mechanisms and risk factors are not yet applied/implemented at scale to delay the progression of frailty in community-dwellers. The Australian Frailty Network (AFN) is a national collaborative group of researchers, clinicians, non-government organisations, consumers and policymakers, in which the engagement and active involvement of consumers has been embedded from the outset. The AFN aims to generate new knowledge to improve health outcomes, to ensure evidence-based management is translated into clinical practice and to build capacity in multidisciplinary and translational frailty research. Here, we describe the development of the AFN, highlighting important milestones: (i) securing funding for the network and flagship elements; (ii) an inaugural summit to establish the strategic vision, values and scope with end-users; (iii) sabbatical visits to learn from international examples; and (iv) developing the governance structure and an actionable plan encompassing consumer engagement, research, education and policy and practice to maximise impact.

Into the virtual worlds: conceptualizing the consumer‐avatar journey in virtual environments

AbstractAs digital representations of human controllers, consumer‐avatars play a pivotal role in enabling immersive consumer experiences in virtual environments. Despite their significance in digital marketing research, the literature on consumer‐avatars is highly fragmented and lacks comprehensive analysis across studies. To address this gap, we conducted a systematic literature review and developed a comprehensive conceptual framework of the consumer‐avatar journey, encompassing three unique phases: Self Representation, Avatar Embodiment, and Avatar‐Mediated Interactions. By integrating empirical evidence with multiple theoretical perspectives, including motivation, self‐concept, identification, and presence theories, we explored consumer motivations for self representation, how avatar identification occurs, and how avatar‐mediated interactions are facilitated by the sense of presence. Additionally, we examined the moderating roles of technological, social, and individual factors in these processes. Our study provides significant theoretical contributions to the current literature by consolidating fragmented research and offers practical insights for marketers to design effective strategies around consumer‐avatars. By elaborating on each phase of the consumer‐avatar journey, we developed 11 propositions and 5 research questions to guide future research on consumer‐avatars.

Performance analysis of a pilot gasification system of biomass with stepwise intake of air-steam considering waste heat utilization

Although the fixed-bed gasifier is widely used because of their simple structure, easy operation, and strong adaptability to biomass type, its economy is weakened by their low bioenergy conversion ability and heat utilization efficiency. Therefore, a novel biomass gasifier with stepwise intake of air–steam is proposed, which also innovatively integrates the concept of multi-stage utilization of waste heat generated during the gasification process into its design. And a pilot system comprising the novel biomass gasifier with a biomass consumption of 30 kg/h has been built. A series of continuous air-steam gasification experiments on pine wood particles shown that, the high-temperature steam in the reduction zone enhanced the ring opening of aromatic hydrocarbons, decarboxylation, dehydroxylation, and the conversion of long-chain to short-chain hydrocarbons, thus increasing the yield of small-molecule gases. The steam reforming reaction played an active role in increasing the hydrogen content, the gasification gas's production and low calorific value. And the relationship among the reaction rates on the surface of char should be VC + H2O＞VC+2H2O＞VC + CO2＞VC+2H2. The minimum input temperature of steam was 350 °C, otherwise more char would be consumed in the oxidation zone to provide heat. The proposed steam-air gasification system achieved optimal performance with an air-to-steam mass ratio (A/S) of approximately 8, a steam temperature of 400 °C, and an air-to-biomass mass ratio (A/B) of 1.2. The average gas production could reach 2.67 m3/kg, with the average low calorific value of 5.1 MJ/m3. The average hydrogen content could reach 20 %, with the average H2/CO ratio of 2. The average effective gasification efficiency could reach 69.72 %. Compared with air gasification, the proposed air-steam gasification was equivalent to the use of 1 kWh of electricity to produce 2.4 kWh of electricity. Combining market research, the price of steam produced by the proposed system was approximately 70 CNY/t less than when using natural gas. This study aims to provide a technical reference for improving the performance of biomass gasification in practical applications.

EXPRESS: A Call for Afrocentric Decolonial Endogenous Marketing and Public Policy Research and Practice: toward Sustainable Peace and Well-Being in African Societies

EXPRESS: A Call for Afrocentric Decolonial Endogenous Marketing and Public Policy Research and Practice: toward Sustainable Peace and Well-Being in African Societies

MARKETING INNOVATIONS AND PERFORMANCE OF INSURANCE COMPANIES IN NIGERIA: MODERATING ROLE OF INSTITUTIONAL SUPPORT

<p>The adoption of marketing innovations can contribute to the sustainability of a firm. However, research on the types of marketing innovations and their effects is limited. The study examined the dimensions of marketing innovations, their effects on performance of insurance firms, and how institutional support moderates those effects. The population of the study 504 management staff from 56 insurance companies, a sample size of 223 was determined using the Taro Yamane formula for finite population. Empirical data were collected and used to validate the model. Significant positive relationships are identified among each dimension of marketing innovation and performance. The findings are explained through the theoretical lens of resource-based view. Results show that both product and process innovation significantly contribute to the performance of insurance companies. Moreover, the relationship between process innovation and firm performance is significantly moderated by institutional support this is because with a favorable regulatory framework and activities aimed at encouraging innovation in the insurance business, institutional support is critical in easing the adoption and implementation of process changes. Whereas institutional support did not moderate the relationship between product innovation and firm performance. The study recommends that to maximize the significant positive effect of product innovation, Nigerian insurance firms should prioritize market research and client feedback. This study contributes to the literature because it elaborates the conceptualization of marketing innovation and presents the dynamics of institutional support and firm performance. It also provides practical implications on how insurance firms can utilize marketing innovations to achieve business sustainability.</p>

Путешествие между каналами: формирование клиентского опыта в цифровой среде

In modern marketing, researchers are focused on the omnichannel approach due to the growing number of communication channels and sources of consumer information about brands. This paper examines the complexity and multifactorial nature of the omnichannel approach in the formation of customer experience and marketing communications in the digital environment. The article discusses the concept of a “Consumer Journey Map”, which reflects the stages of making a purchase decision, after-sales interaction and the customer experience formed within this path. This approach allows you to define and analyze the touchpoints with the consumer and information messages at each stage of the consumer journey in order to create a positive brand image. The consumer’s journey is formed by the sequential passage of a number of points of contact, which may belong to the brand, its partners or be independent. This affects the degree of brand control over the information at each of these points. Particular attention is paid to the complexity of tracking the entire variety of contact points through which the customer passes on the way to making a purchase. The management of this variety of points from the standpoint of a single communication environment of brand and consumer interaction is the subject of omnichannel marketing research. Within the framework of this study, the author considers the evaluation of the effectiveness of marketing channels at the stage of preparation for purchase. These channels may be underestimated, since in terms of direct return on marketing investments, they lose to the final pre-purchase channels, but they play a key role in shaping the customer experience leading to subsequent purchases. The article presents the results of a study of online communication based on a company providing educational services. This study demonstrates the relationship between the volume of investments in paid promotion channels and the total revenue from online channels. The results of the study emphasize the importance of the omnichannel approach in modern communication, where the buyer interacts with the brand in various channels and perceives communication as a single continuous process, even when switching from one channel to another.

Sentiment Analysis of Nigerian Opinions Using Logistic Regression and Random Forest Algorithms: A Comparative Study

This study investigates the efficacy of Logistic Regression and Random Forest models in sentiment analysis using Nigerian-based datasets, namely "Gangs of Lagos" and "PeterObi Politics." Sentiment analysis, a vital component of Natural Language Processing (NLP), plays a crucial role in understanding public opinion and sentiment trends, particularly in the context of Nigerian socio-political discourse. Leveraging machine learning techniques, the study examines the performance of these models in predicting sentiment classes, including positive, negative, and neutral sentiments, within the datasets. The findings shed light on the strengths and limitations of Logistic Regression and Random Forest in discerning sentiment nuances prevalent in Nigerian language expressions with Logistic Regression outperforming Random Forest in both cases. This research contributes to the advancement of sentiment analysis methodologies tailored to Nigerian linguistic and cultural contexts, with implications for various applications, including social media monitoring, political analysis, and market research.

The Role of Clothing Technology in Supporting Sustainable Fashion in the Post-COVID-19 Era

With the outbreak and ongoing spread of the COVID-19 pandemic, a wave of post-COVID-19 zeitgeist has emerged worldwide. From the perspective of fashion trends, an increasing number of consumers are demanding higher standards of health, environmental friendliness, and sustainability. Over the past 10 years, the integration of technology in clothing has facilitated continuous updates in both functionality and aesthetics. This article aims to explore the relationship between clothing technology and sustainable fashion in the post-COVID-19 era, seeking to enhance the development and innovation of sustainable fashion through the empowerment of clothing technology. This study conducts extensive research on the literature and online case studies, categorizing empowered sustainable fashion technology design cases into six major categories and four directional themes. It introduces an innovative sustainable fashion design assessment model, PCBS (Product, Customer, Business, Society). Subsequently, the knowledge framework is applied in design practice alongside consumer research to validate the system’s usability. Furthermore, this research synthesizes and summarizes the methods through which fashion technology can support sustainable fashion in the post-pandemic era. Designers and practitioners can reference these insights for more advanced sustainable design initiatives, thereby promoting a lower-carbon and environmentally friendly system that drives global innovation and development in a sustainable society.

Using necessary condition analysis to complement multigroup analysis in partial least squares structural equation modeling

With the growing importance of partial least squares structural equation modeling (PLS-SEM) in marketing and consumer research, the use of Multigroup Analysis (MGA) for discovering observed heterogeneity (i.e., differences in relationships between variables for subgroups of the population under investigation) and deriving relevant operational results has become of great interest. However, these analyses are based exclusively on an additive sufficiency logic and do not permit researchers to test and validate hypotheses drawing on a necessity logic, the latter having been the focus of recent significant developments. Addressing this concern, the present paper offers guidelines for combining the use of Necessary Condition Analysis (NCA) and MGA performed with PLS-SEM. Taken together, these analyses can explore and improve knowledge about predefined subgroups of interest, enhance the understanding of relationships, refine the role of specific key antecedents by discovering meaningful necessary conditions, and therewith, contribute to theorizing. An empirical illustration drawing on the relationship between corporate social responsibility and customer loyalty is developed in a step-by-step fashion to provide marketing researchers with the guidelines to conduct the MGA and NCA, and finally report and interpret the results in accordance with both the sufficiency and the necessity logics. This integrative procedure contributes to the advancement of PLS-SEM applications. By delivering a better understanding of the group-specific results of a PLS-SEM–based MGA in a necessity logic, it promotes the complementary usage of sufficiency and necessity logics and therefore helps researchers to uncover novel theoretical and practical results when evaluating the data.

The consumer-object relationship debate in contemporary technoculture: a systematic review for a theory of the object

ABSTRACT This paper systematises the theoretical perspectives that inform the consumer-object relationship (C-OR) debate and its evolutionary trajectories to organise how a theory of the object has been developed in marketing and consumer research. We build on a diachronic critical reading of the key turning points in the debate to conduct a systematic review, combining a bibliometric and semantic-lexicographic analysis. Our analysis organises the contribution that each theoretical perspective offered to the development of a theory of the object, highlighting the interplays, contrasts, mesh-ups, and distinctions in terms of theoretical underpinnings, vocabularies, and ideological viewpoints. In so doing, it raises awareness about the significance of embracing diverse theoretical perspectives to guide further inquiry on the expanding role of smart and technological objects in C-OR.

Corporate sustainability research in marketing: Mapping progress and broadening our perspective

Corporate sustainability research in marketing: Mapping progress and broadening our perspective

The Impact of Artificial Intelligence for Advancement in Entrepreneurial Education

The changing technology has advanced into new advents like Artificial Intelligence. This technology has diffused into the classrooms through chatbots like ChatGPT, Claude, Google Bard, YouChat, KoalaChat, ChatOn, Microsoft Binge and many others. The conventional softwares are only updated by humans while Artificial Intelligence can correct and remodel itself. Artificial Intelligence is assisting the entrepreneurial organizations and students in data analysis, automation and Natural Language Processing (NLP). It also helps the entrepreneurial organizations in strategic decision making and managing operations and accounts. This research focuses on the opportunities and challenges posed by Artificial Intelligence in the entrepreneurial education across various business schools. It examines the benefits of chatbots for educational purposes. It also studies the limitations of chatbots. It enquires about the business advice sought from chatbots. For this purpose, a survey was applied amongst students of entrepreneurial courses to analyze the impact of Artificial Intelligence in our classrooms. It is a study performed on 103 students enrolled in entrepreneurship courses at two management institutes of India between August, 2023, and December, 2023. The study focuses on the benefits of AI in areas such as assisting in classroom activities like such as market research, competitor analysis and legal aspects. It also aids the students in getting feedback for their assignments, preparing for examinations and rapid access to information. The research suggests that Artificial Intelligence is significantly contributing right from idea generation, planning, forecasting and progress evaluation of business plans to entrepreneurial students. It is extensively helping the entrepreneurial students in developing the business model canvas which assists them in designing the blueprint of the project, strategic management, and development of innovative business models. It also assists in improving the productivity and efficiency of students. This research would facilitate students, teachers and business schools imparting entrepreneurial curriculum inculcate Artificial Intelligence into the classroom studies.

The Quality of Blume and Vasicek Betas for forecasting systematic risk: Evidence from a German stock portfolio

Abstract In both practical applications and empirical capital market research the beta factor is often estimated for the future period using an OLS regression analysis based on historical data. However, these betas are often not reliable for the future. For this reason, methods have been developed to correct or adjust the (raw) beta. The aim of this study is to find out to what extent the forecasting quality of a stock beta can be improved by Blume Beta, Vasicek Beta and a simple variant of Blume Beta ("Adjusted Beta"). For this purpose, an empirical analysis is carried out on the basis of 10 stocks included in the German stock index DAX. For the entire period under review, it can be observed that all three adjustment methods tend to improve the forecast quality compared to the raw beta, with the simple “Adjusted beta” leading to the best values. The examination of two subperiods, one covering the financial and economic crisis of 2008/2009 and the other the Corona pandemic, shows that the forecasting quality tends to be lower when looking at individual stocks compared with the overall period. However, according to the values (i.e. averages of all stocks) of the forecasting quality measures used in this paper, the adjustment procedures mostly produce better values than raw beta in both subperiods. JEL classification numbers: G11. Keywords: Adjusted beta, Blume beta, Vasicek beta, Mean Squared Error.

Digital transformation, ESG responsibility and corporate's export performance

This study examines the effect of digital transformation on firms’ export performance between 2013 and 2021 by using information from the China Stock Market & Accounting Research Database. We find that digital transformation is positively correlated with firms’ export performance. Moreover, firms’ Environmental, Social, and Governance responsibility plays an important role in this process; specifically, environmental and social responsibility practices can significantly enhance firms’ export performance, whereas the influence of firms’ governance remains relatively minor. These findings contribute to a deeper understanding of the impact of digital transformation on Chinese listed firms’ export decisions and provide valuable insights for policymakers.

Lifecycle Management of Generic product in US market

In the US Market, lifecycle management for generic products includes developing and implementing plans to maximize an item’s market potential from launch to decline. It starts with market research and approval of regulatory involving submission of an Abbreviated New Drug Application (ANDA) to demonstrate bioequivalence to the branded product followed by comprehensive market analysis to identify opportunities and assess rivals. Companies use aggressive pricing and marketing techniques to swiftly increase their market share after a product is approved. Continuous monitoring and adaptability to changes in the market, updates to regulations, and competitive actions are crucial throughout the lifecycle. This review focuses on Market entry strategy, Product launch, Market landscape of Generic Drugs in US.

Why Did You Stop? Reasons for Stopping Faking Orgasms and Its Association with Sexual, Relationship, and Life Satisfaction in Denmark, Finland, France, Norway, Sweden, and the UK

ABSTRACT The current study investigated the phenomenon of faking orgasms, including the reasons why people stop faking orgasms, sociodemographic predictors of faking orgasms, its association with sex toy use, and its association with sexual, relationship, and life satisfaction. A cross-country convenience sample of 11,541 respondents from six European countries (Denmark, Finland, France, Norway, Sweden, and the UK) was collected in May and June 2022 through respondent panels by Cint, a market research software platform. Participants completed an online self-report survey. The study’s main findings showed that around 51% of men and women in the study had never faked orgasms, around 28% had faked orgasms but stopped faking and around 13% currently faked orgasms. Further, the reasons for men and women to stop faking orgasms included becoming more comfortable with not having an orgasm, improving sexual communication with their sexual partner, and the partner paying more attention to the respondents’ desires and preferences. Finally, it was shown that faking orgasms was associated with lower sexual, relationship, and life satisfaction. The current study represents one of the few research projects focusing on the phenomenon of stopping faking orgasms and reasons for it, with the added strength of including a large male sample.

Does social media contribute to research impact? An Altmetric study of highly-cited marketing research

The thorough dissection of prominent scholarly contributions can shed light on the evolution of research trajectories. Using marketing research as a case, this study aims to probe into the recognition and resonance that research enjoys across social media landscapes, employing the power of Altmetric. We employed an analytical approach involving descriptive statistics coupled with the Spearman correlation test, scrutinizing Altmetric data for the most heavily cited works in the marketing discipline (n: 137). Our examination illuminates that the United States and the United Kingdom are the dominant contributors to the majority of tweets and readership relating to these works. Noteworthily, marketing research featured in top-tier publications registered the highest Altmetric scores from both Twitter and Mendeley. An intriguing pattern surfaced in our exploration, highlighting a positive relationship between Altmetric scores drawn from social media platforms and citation counts on the Web of Science (WoS), as well as between Mendeley readership and WoS citations. These Altmetric insights underscore the pivotal role social media plays in propelling citation rates of research, implying that researchers can significantly amplify the visibility and citation impact of their work by strategically employing social media platforms and tapping into Altmetric indicators’ potential.

HINTs: Sensemaking on large collections of documents with Hypergraph visualization and INTelligent agents.

Sensemaking on a large collection of documents (corpus) is a challenging task often found in fields such as market research, legal studies, intelligence analysis, political science, or computational linguistics. Previous works approach this problem from topic- and entity-based perspectives, but the capability of the underlying NLP model limits their effectiveness. Recent advances in prompting with LLMs present opportunities to enhance such approaches with higher accuracy and customizability. However, poorly designed prompts and visualizations could mislead users into falsely interpreting the visualizations and hinder the system's trustworthiness. In this paper, we address this issue by taking into account the user analysis tasks and visualization goals in the prompt-based data extraction stage, thereby extending the concept of Model Alignment. We present HINTs, a VA system for supporting sensemaking on large collections of documents, combining previous entity-based and topic-based approaches. The visualization pipeline of HINTs consists of three stages. First, entities and topics are extracted from the corpus with prompts. Then, the result is modeled as a hypergraph and hierarchically clustered. Finally, an enhanced space-filling curve layout is applied to visualize the hypergraph for interactive exploration. The system further integrates an LLM-based intelligent chatbot agent in the interface to facilitate the sensemaking of interested documents. To demonstrate the generalizability and effectiveness of the HINTs system, we present two case studies on different domains and a comparative user study. We report our insights on the behavior patterns and challenges when intelligent agents are used to facilitate sensemaking. We find that while intelligent agents can address many challenges in sensemaking, the visual hints that visualizations provide are still necessary. We discuss limitations and future work for combining interactive visualization and LLMs more profoundly to better support corpus analysis.

Essential Steps and Strategic Considerations for Successfully Launching a Small-Scale Business

To achieve a successful launch of a small-scale firm, one must carefully navigate through many crucial procedures and strategic considerations. This review essay thoroughly analysed the fundamental activities and techniques required for a successful company’s commencement. Essential elements include completing comprehensive market research to find possibilities and comprehend competition, formulating a comprehensive business plan that delineates objectives, strategies, financial forecasts, and operational plans, and obtaining sufficient finance. The research highlighted the significance of robust financial management methods, including budgeting, cash flow management, and financial forecasting, to guarantee stability and facilitate development. Efficient allocation of resources, adaptation to market changes, and harnessing technology were important strategic considerations for overcoming common difficulties and attaining lasting success. The essay consolidated the latest research and optimal methodologies, offering practical insights for entrepreneurs to improve their company performance and overcome frequent challenges. Suggestions included consulting with specialists, being attentive to market fluctuations, and enhancing the availability of financial resources and support networks. This exhaustive analysis provided a beneficial structure for small-scale enterprises seeking to develop a robust basis for expansion and long-term sustainability. Keywords: Small-scale business, Business launch, Market research, Business plan, Financial management.

A Mini Review on the Opportunities for Membrane Pervaporation Technology for Energy-efficient Removal of Dispersed Oil and Dissolved Hydrocarbons from Produced Water

Produced water is reported to have the largest volume of waste stream associated with hydrocarbon recovery. It was estimated to increase from 250 million B/D in 2007 to more than 300 million B/D between 2010 and 2012. Market research conducted by Adroit put the globally produced water treatment market at a value of USD 5.10 billion in 2022. This value is anticipated to be USD 9.80 billion in 2032 at a compound annual growth rate (CAGR) of 5.80% over the prediction period. Oil and gas companies have been mandated to comply with the newly enacted environmental regulations that require extensive treatment of this water before discharge or reuse. The limited quantity of freshwater resources coupled with the increasing oil and gas production activities has made it necessary for all stakeholders to look for sustainable management of this water. Presently, a certain percentage of produced water is reused while the rest is discharged into the ocean. In both cases, the water needs to be thoroughly treated. The choice of technologies for produced water treatment depends on numerous factors, such as the chemical composition of the water and the level of purity that must be attained before disposal, recycling, or re-use. Some of the technologies used for produced water treatment include physical separation methods such as gravity, adsorption, filtration, coalescence, cyclones, flotation, centrifuges, membranes, and oxidation. There are also chemical and biological separation methods. Contaminants such as small droplets of dispersed oil and dissolved hydrocarbons (DODHs) are very challenging to remove using the above-listed water treatment technologies. Moreover, the use of membrane technology has been limited only to the use of reverse osmosis and membrane filtration for removing salinity, metals, and other inorganics. This article highlights the opportunities for the use of membrane vapor permeation and pervaporation for the removal of the small droplets of DODHs, which have been reported to be very challenging contaminants to remove. The use of 3D printing technology for the fabrication of membrane materials was reviewed. The 3D membrane development method can be used to fabricate almost any shape of the material in a highly customized manner using computer-aided design. The information presented in this article will serve as a useful reference for the technologies used for a sustainable water treatment strategy in the oil and gas industry.