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High-resolution remote sensing images possess a wealth of semantic information. However, these images often contain objects of different sizes and distributions, which make the semantic segmentation task challenging. In this paper, a bidirectional feature fusion network (BFFNet) is designed to address this challenge, which aims at increasing the accurate recognition of surface objects in order to effectively classify special features.

There are two main crucial elements in BFFNet. Firstly, the mean-weighted module (MWM) is used to obtain the key features in the main network. Secondly, the proposed polarization enhanced branch network performs feature extraction simultaneously with the main network to obtain different feature information. The authors then fuse these two features in both directions while applying a cross-entropy loss function to monitor the network training process. Finally, BFFNet is validated on two publicly available datasets, Potsdam and Vaihingen.

In this paper, a quantitative analysis method is used to illustrate that the proposed network achieves superior performance of 2–6%, respectively, compared to other mainstream segmentation networks from experimental results on two datasets. Complete ablation experiments are also conducted to demonstrate the effectiveness of the elements in the network. In summary, BFFNet has proven to be effective in achieving accurate identification of small objects and in reducing the effect of shadows on the segmentation process.

The originality of the paper is the proposal of a BFFNet based on multi-scale and multi-attention strategies to improve the ability to accurately segment high-resolution and complex remote sensing images, especially for small objects and shadow-obscured objects.

This research aims to comprehend the factors that impact the emerging inclination of consumers toward mobile finance technology (fintech) services over banking institutions. The study focuses on users' demographics and psychographics to delineate their unique segments and profiles.

The study proposes a segmentation and profiling framework that includes variance analysis, two-step cluster analysis and pairwise statistical tests. This framework is applied to a dataset of customers using a range of mobile fintech services, specifically robo-investment, peer-to-peer (P2P) payments, robo-advisory and digital savings. The analysis creates distinct customer profile clusters, which are later validated using pairwise statistical tests based on segmentation output.

Empirical results reveal that P2P payment service users exhibit a higher frequency of usage, proficiency and intention to continue using the service compared to users of robo-investment or digital savings platforms. In contrast, individuals utilizing robo-advisory services are identified to have a significantly greater familiarity and intention to sustain engagement with the service compared to digital savings users.

The findings provide financial institutions, especially traditional banks with actionable insights into their customer base. This information enables them to identify specific customer needs and preferences, thereby allowing them to tailor products and services accordingly. Ultimately, this understanding may strategically position traditional banks to maintain competitiveness amidst the increasing prominence of fintech enterprises.

This research provides an in-depth examination of customer segments and profiles within the mobile fintech services sphere, thus giving a nuanced understanding of customer behavior and preferences and generating practical recommendations for banks and other financial institutions. This study thereby sets the stage for further research and paves the way for developing personalized products and services in the evolving fintech landscape.

This study aims to develop a practical and effective approach for market segmentation using customer experience dimensions derived from online reviews.

The research investigates over 6,500 customer evaluations of food establishments on Taiwan’s Yelp platform through the Latent Dirichlet allocation (LDA) data mining approach. By using the LDA-derived experience dimensions, cluster analysis discloses market segments. Subsequently, sentiment analysis is used to scrutinize the emotional scores of each segment.

Mining online review data helps discern divergent and new customer experience dimensions and sheds light on the divergent preferences among identified customer segments concerning these dimensions. Moreover, the polarity of sentiments expressed by consumers varies across such segments.

Analyzing customer attributes extracted from online reviews for segmentation can enhance comprehension of customers’ needs. Further, using sentiment analysis and attributes of online reviews result in rich profiling of the identified segments, revealing gaps and opportunities for marketers.

This research presents a new approach to segmentation, which surmounts the restrictions of segmentation methods dependent on survey-based information. It contributes to the field and provides a valuable means for conducting customer-focused market segmentation. Furthermore, the suggested methodology is transferable across different sectors and not reliant on particular data sources, creating possibilities in diverse scenarios.

This case study covers marketing concepts, including marketing mix, segmentation, targeting and brand positioning and communication. After completion of the case study, the students will be able to understand the importance of segmentation and targeting; recognize the differences between business-to-business (B2B) and business-to-customers (B2C) segments; gain knowledge about the points of parity and points of difference while positioning; and examine the elements of a marketing mix.

The case centered around Mr. Ashvinder Singh, founder and director of Uni Style Image (USI), who initiated the polo T-shirt business in 1990 in Okhla, Delhi. The brand expanded across the country, but from 2010, USI faced fluctuating demand due to the rise of online marketing and intense competition from global fashion brands. Revenues dropped massively, leading to a significant downsizing from over 300 employees to just 11 by the end of fiscal year 2016–2017. In 2018, Singh explored the B2B model; however, the onset of the COVID-19 pandemic in 2020 impacted many small- and mid-sized apparel businesses, including USI. In the fiscal year 2021–2022, the B2B segment accounted for 90% of total revenue, but the business size could not cover significant operating expenses. Despite only 10% of revenue coming from the B2C segment, Singh wanted to leverage the online space. In September 2022, Singh closed his factory in Noida, National Capital Region, Delhi. Amid the uncertainty, Singh explored various opportunities in the Indian market. In 2023, he even engaged a consultancy for expertise in marketing initiatives. He had to choose the target segment/s, develop a positioning strategy and create an effective marketing mix with very limited resources.

This case is designed for undergraduate and postgraduate students, offering a valuable teaching tool for essential marketing concepts, such as the marketing mix, segmentation, positioning and brand communication. It can be used in both core marketing courses and elective courses like brand management, consumer behavior and integrated marketing communication. The decision dilemma presented in the case enriches the understanding of these concepts, making it a valuable resource for marketing education.

Teaching notes are available for educators only.

CSS 8: Marketing.

This paper presents a decision-making framework for e-banking operations, based on the Quality Function Deployment and the Analytic Hierarchy Process. The main research question is the development of a framework and its potential contributions in supporting decision makers in implementing quality strategies that will encourage the usage of e-banking services (EBS).

The introduced framework comprises four distinct stages which include criteria determination, field surveys and EFA, QFD application including AHP and finally sensitivity analysis investigating the dynamic nature of the environment. AHP determines the intensity of the relationship between e-banking quality criteria and customer banking activities. A novel House of Quality (HoQ) is proposed, based on a market mix founded on key e-banking activities, and sensitivity analysis is used to investigate alternative scenarios. To illustrate the steps of applying this framework, the authors use a convenience sample from the Greek e-banking sector.

Through the illustrated example is supported that the proposed approach can reveal valuable information when contemplating strategies to improve e-banking usage and expand its acceptance. In addition, sensitivity analysis leads to purposeful insights regarding the effects of market segmentation and/or target settings on the ranking of e-banking quality/selection criteria provided by the HoQ. In the specific numerical example, the most critical quality factors were “Security and Reliability”, “Convenience”, “Design”, “Pricing” and “Skills,” although different rankings night well appear in different contexts or geographical regions. Moreover, sensitivity analysis showed that these results depend on the specific market mix and targets. As mentioned above, the implementation of the framework in different geographical regions or e-service sectors might certainly reveal different critical factors.

Discussed in the paper body.

Discussed in the paper body.

The paper presents a well-defined four stage framework for improving EBS penetration. It utilizes a structured qualitative and quantitative approach and outlines and ranks e-banking quality factors stemming from the market mix and allows assessment of alternative scenarios through sensitivity analysis.

Based on the case study of an SME company in the United Kingdom (which we will call SweetStar Cloud), this paper examines the attempts of the company to achieve significant strategic change. The company is attempting to move from being a tradition managed service provider of information services towards becoming a significant influencer in the market for digital services in the UK. As part of a knowledge transfer partnership (KTP), a local UK University has been closely involved in developing this new strategic direction and it is well poised to present and analyse the story. From the use of tried and tested strategic tools, including Porter's generic strategies and segmentation and targeting, the company has also embraced digital-specific approaches for developing partnerships with clients, developing pilot projects and experimenting with its use of social media. At the heart of this research is an analysis of the move from push marketing towards models of attraction. This paper aims to explore how traditional strategic tools are still applicable in the digital era alongside new tactical approaches in the digital sector. This aim has led to an approach to business that is responsible, in terms of moving away from a traditional push-selling model to one of partnership with customers at a strategic level. Strategy in dynamic markets often highlights responsiveness as a key success factor. The ability to respond (a response-ability) requires more agile companies. As SweetStar Cloud has developed its strategy, it has focused in achieving this more effective ability to respond through a more collaborative approach. In this sense, agile response-ability converges with business responsibility, as new abilities in communication, cooperation and trust development become key.

Purpose: This chapter aims to find the impact of cultural marketing on consumer buying behaviour and analyse the cultural factors affecting consumers’ buying behaviour. Cultural marketing aims to offer and promote a product, a message, or a service to a group of people who may be their potential purchasers and belong to the same culture or particular demographic.

Methodology: This study uses the published research for different countries viz. India, Canada, Germany, the UAE, the UK, the USA, Japan, etc., in the field of culture, cross-culture, and consumer buying behaviour considering various factors and their impact; but in particular, this study focussed on the cultural factors only and analysed their impact on the consumer behaviour of the different countries.

Findings: The study revealed that different countries have their own unique culture. Cultural factors have a positive relationship with consumers’ buying behaviour and exhibit that consumers behave differently towards the same product as per their perception developed by their culture.

Need of the study: Today, the world has become global, and to become a successful consumer oriented market service provider, marketers have to study the psychology of the customers to procure them. This study focusses on one of the essential factors, that is, culture and how cultural factors affect consumer buying behaviour. The study of culture is the gateway to attracting consumers in the market.

Practical implications: The study would help multinational companies in segmentation, targeting, and positioning and developing several marketing strategies for their products. Companies would be able to understand changes in consumer purchasing behaviours that arise from cultural differences, which helps them cater to the needs of their global consumers.

The primary aim of this study is to gain insight into the entrepreneurial marketing strategy (EMS) decisions made by microenterprises in the craft sector and draw comparisons between the marketing strategy formulation and implementation of conventional businesses and those of craft-based microenterprises with a specific focus on the context of emerging markets, particularly India.

This paper follows a qualitative interpretivist paradigm using a multiple-case methodology approach. It tracks craft-based microenterprises that make furniture or home décor products in India. The study participants were the founders, principal designers, studio managers or craftspersons.

This study’s findings reveal that craft-based microenterprises implement an EMS that adopts a hybrid form of market orientation strategy. In this approach, the product or creative concept is at the centre of the decision-making, and the customer needs are factored in at a later stage for customisation. These microenterprises prioritise product positioning over segmentation and targeting strategies.

This study tries to understand marketing strategy decision-making processes among craft-based microenterprises in India. Given that study participants came from only two-product-based craft businesses, this limits the generalisability of the findings to similar or related contexts. This study provides a framework and methodology for replication in other contexts and industries to formulate a nuanced understanding of micro, context-specific, craft-based businesses.

This study uses qualitative analysis to understand EMS in craft-based businesses in India. This study contributes to this fledgling stream of literature at the interface of marketing and entrepreneurship to understand entrepreneurial marketing. This study analyses the marketing strategy of craft-based businesses using the framework of Morgan et al. (2019).

The purpose of this paper is to explore the prospect of using neurophenomenology to understand, design and test phygital consumer experiences. It aims to clarify interpretivist approaches to consumer neuroscience, wherein theoretical models of individual phenomenology can be combined with modern neuroimaging techniques to detect and interpret the first-person accounts of phygital experiences.

The argument is conceptual in nature, building its position through synthesizing insights from phenomenology, phygital marketing, theoretical neuroscience and other related fields.

Ultimately, the paper presents the argument that interpretivist neuroscience in general, and neurophenomenology specifically, provides a valuable new perspective on phygital marketing experiences. In particular, we argue that the approach to studying first-personal experiences within the phygital domain can be significantly refined by adopting this perspective.

One of the primary goals of this paper is to stimulate a novel approach to interpretivist phygital research, and in doing so, provide a foundation by which the impact of phygital interventions can be empirically tested through neuroscience, and through which future research into this topic can be developed. As such, the success of such an approach is yet untested.

Phygital marketing is distinguished by its focus on the quality of subjective first-personal consumer experiences, but few papers to date have explored how neuroscience can be used as a tool for exploring these inner landscapes. This paper addresses this lacuna by providing a novel perspective on “interpretivist neuroscience” and proposes ways that current neuroscientific models can be used as a practical methodology for addressing these questions.

This study aimed to identify subgroups of esports players based on their gaming behavior patterns across game genres and compare self-efficacy, social efficacy, loneliness and three dimensions of quality of life between these subgroups.

324 participants were recruited from prolific academic to complete an online survey. We employed latent profile analysis (LPA) to identify subgroups of esports players based on their behavioral patterns across genres. Additionally, a one-way multivariate analysis of covariance (MANCOVA) was conducted to test the association between cluster memberships and development and well-being outcomes, controlling for age and gender as covariates.

LPA analysis identified five clusters (two single-genre gamer groups, two multigenre gamer groups and one all-genre gamer group). Univariate analyses indicated the significant effect of the clusters on social efficacy, psychological health and social health. Pairwise comparisons highlighted the salience of the physical enactment-plus-sport simulation genre group in these outcomes.

This study contributes to the understanding of the development and well-being benefits experienced by various esports consumers, as well as the role of specific gameplay in facilitating targeted outcomes among these consumer groups.