Customer Demographics Research Articles

Understanding the predictability of user demographics from cyber-physical-social behaviours in indoor retail spaces

Understanding the association between customer demographics and behaviour is critical for operators of indoor retail spaces. This study explores such an association based on a combined understanding of customer Cyber (online), Physical, and (some aspects of) Social (CPS) behaviour, at the conjunction of corresponding CPS spaces. We combine the results of a traditional questionnaire with large-scale WiFi access logs, which capture customer cyber and physical behaviour. We investigate the predictability of user demographics based on CPS behaviors captured from both sources. We find (1) strong correlations between users’ demographics and their CPS behaviors; (2) log-recorded cyber-physical behavior reflects well data captured in the corresponding questionnaire; (3) different CPS behaviors contribute differently to the predictability of demographic attributes; and (4) the predictability of user demographics from logs is comparable to questionnaire-based data. As such, our study provides strong support for demographic studies based on large-scale logs data capture.

Predicting product co-consideration and market competitions for technology-driven product design: a network-based approach

We propose a data-driven network-based approach to understand the interactions among technologies, products, and customers. Specifically, the approach enables both a qualitative understanding and a quantitative assessment of the impact of technological changes on customers’ co-consideration behaviors (decision of cross-shopping) and as a consequence the product competitions. The uniqueness of the proposed approach is its capability of predicting complex co-consideration relations of products as a network where both descriptive analyses (e.g., network statistics and joint correspondence analysis) and predictive models (e.g., multiple regressions quadratic assignment procedure) are employed. The integrated network analysis approach features three advantages: (1) It provides an effective visual representation of the underlying market structures; (2) It facilitates the evaluation of the correlation between customers’ consideration preferences and product attributes as well as customer demographics; (3) It enables the prediction of market competitions in response to potential technological changes. This paper demonstrates the proposed network-based approach in a vehicle design context. We investigate the impacts of the fuel economy-boosting technologies and the turbocharged engine technology on individual automakers as well as the entire auto industry. The case study provides vehicle engineers with insights into the change of market competitions brought by technological developments and thereby supports attribute decision-making in vehicle design.

Online Customer's Trust: A Methodological and Thematic Review

With the advent of technology there have been major changes that Indian market has witnessed. A massive change has been witnessed in the shopping experiences of customers. Buying from Brick and mortar store to shifting to online stores has been one of the examples to explain the same. But what really influences a customer to buy online? The research paper discusses the various factors that influence the customer's decision. The review paper is a mix of qualitative and quantitative research that is based on non-empirical research. The research highlights the factors that affect the online customer trust and there are major indicators like E WOM, Attitude to technology, life style based purchases which have been highlighted in the paper. Some other factors like increased competition, prior customer purchase, demographics, and ecommerce institutional mechanisms have not been explained in detail but can be undertaken for future research. The paper major focus has been the role that customer trust has on the ecommerce platform.

Customer engagement in CSR: a utility theory model with moderating variables

PurposeBoth customer engagement (CE) and corporate social responsibility (CSR) have been linked to customer loyalty. Past studies use service dominant logic and customer value co-creation to explain this relationship. The purpose of this paper is to apply utility theory to develop and test a new theoretical model based on CSR initiative preference to understand the relationship between CE and customer loyalty to the organisation in a CSR platform.Design/methodology/approachThis empirical study uses choice theory in the form of best-worst scaling, and structural equation modelling, to measure the impact of sports club members’ choice preferences for a range of CSR initiatives on their intention to engage with the initiative and subsequent loyalty to the club.FindingsThis study highlights the importance of engaging members in the CSR strategy they prefer as it enhances not only the extra value to the organisation via customer loyalty to the organisation, but also CE with the organisation. Furthermore, the study reveals age and gender impact on the relationship between CE in CSR initiatives and customer loyalty.Originality/valueThis study extends CE to CSR behaviours and provides empirical evidence for a unique theoretical framework of CE based on utility theory. It also highlights the need to take into account moderating variables such as customer demographics.

The Cross Section of Bank Value

We study the determinants of value creation in the cross section of U.S. commercial banks. We develop novel measures of individual bank's productivities at collecting deposits and making loans. We relate these measures to bank market values and find that variation in deposit productivity explains the majority of cross-sectional variation in bank value. We show that variation in productivity is driven by differences across banks in technology, customer demographics, and market power. We also find evidence of synergies between deposit-taking and lending. Our findings suggest that there is significant heterogeneity in banks' abilities to capture value by manufacturing safe assets.

Reserved airport parking: A creative parking product to enhance revenue and improve service

Airports are continually seeking new and innovative ways to improve customer flow efficiencies while simultaneously maximising non-airline revenue. A reserved parking programme can facilitate efficient customer movement beginning with airport arrival through the access point of the airport terminal. When implementing the reserved parking programme at Denver International Airport (DEN), several factors were taken into consideration, including customer demographics, physical infrastructural layout and configuration. Once implemented, the programme at DEN has shown that reserved parking caters to not just the typical business traveller, but to customers who may not have been thought would take advantage of a reserved parking product enhancement. Realising the full benefits of a reserved parking programme required a well thought out design in order to allow for maximum financial and operational flexibility.

Retail Promotion and Advertising in the Green Industry: An Overview and Exploration of the Use of Digital Advertising

The retail portion of the green industry, valued at $50.55 billion, continues to provide a major connection between the industry and consumers. Given the importance of retailers in the green industry and little research exists that documents their advertising practices and impacts, the 2013 Trade Flows and Marketing Practices survey included questions to capture data for retail-only firms. This paper reports on the percentage of sales retailers allocate to promotion and advertising, including a breakdown of media used; point-of-sale (POS) materials and how they are acquired; how green industry retailers are using social media and mobile marketing [in particular, quick response (QR) codes]; the methods retailers use to collect customer demographics; customer loyalty programs (CLP); and how they are managed by retailers and a comparison of retail firms’ advertising practices by size of firm. A combination of mailed and Internet-distributed surveys resulted in a total of 699 useable retail business responses with greater than or equal to $1000 in annual revenue. The median expenditure as a percentage of sales on advertising was 3.6% for all retail firms responding with 33.7% spending no dollars on advertising. In examining the distribution based on media type, the Internet was the most frequently listed by firms (32.3%) with a mean expenditure of 42.5% of total advertising dollars. Social media was listed second most frequently (21.5%) with a mean expenditure of 29.6%. Newspapers were listed as the third most frequently used type of media (18.0%). Social media use is strong and among social media platforms, Facebook (60%) far exceeds any other platform. A third of the respondents (34.2%) reported the use of POS materials. A very small percentage of firms (3.0%) reported using QR codes and 19.4% reported having a CLP. Of those, 45.8% used customer purchase cards, whereas 35.4% used POS software. Nearly 33% of the firms collected demographic information about their customers. Of those, the method with the highest percentage use (multiple responses were permitted) was social media (50.7%) followed by CLP (48.9%), web visits (34.5%), questionnaires (15.7%), social coupons (13.5%), census data (3.9%), and marketing firms (3.1%). There were firm-size differences in seasonal employees and mean sales per employee with large firms having greater numbers than hobby, small- or medium-sized firms. There were no differences in the percentage of advertising media allocations based on firm size, but large firms used web visits, social coupons, and social media more than other types of firms to collect customer demographics. While, green industry retailers are currently using social media for marketing green industry goods, they have much more opportunity to use electronic media for CLPs and to begin using QR codes or other mobile-centric technologies to deliver in-store promotional information to consumers.

The impact of perceived crowding on customer satisfaction

Abstract Purpose The purpose of this paper is to develop and test an explanatory model of how perceived crowding and coping behavior impacts upon customer satisfaction. The paper contributes to the service management literature by; 1) identifying key factors impacting crowding perception in a winter sport outdoor setting; 2) highlighting its influence on customer satisfaction; and 3) advocating the need for winter destination managers to overcome perceived crowding. Design/methodology/approach The paper applied a quantitative methodology to explore the relationship between customer demographics, coping mechanisms and customer satisfaction. This data is utilized to highlight management issues to overcome perceived crowding. Findings The theoretically developed and empirically tested model proves that perceived crowding in winter sport settings is influenced by a number of different factors, such as a customer’s demography. Perceived crowding leads to coping behavior that in turn increases the crowding perception of affected people. Perceived crowding and coping behavior both negatively influence customer satisfaction in a winter outdoor setting. Research limitations/implications The most significant limitation of the paper are the non-random sampling approach, the rather small sample size, the selected factors in the presented model, as well as the nature of the services (outdoor experiences) explored in this paper. Originality/value The paper is the first to explore the constructs of crowding, coping behavior and visitor satisfaction for a winter sports outdoor setting. Results show that crowding is an important construct for service sector managers to recognize and manage in order to overcome an increase in dissatisfied visitors.

A Local Pub Tries To Keep Up With Changing Preferences

Jim Foster and his father started an Irish pub, The Selwyn Pub, in an upscale neighborhood of Charlotte, North Carolina. Originally envisioned as a casual dining restaurant with an Irish pub like atmosphere, Jim and his father soon discovered that their customers were looking for a place to drink beer and eat pub food. Recently, they noticed a shift in the customer demographics and drinking preferences at the Pub. Seeing a significant growth in the number of women that frequented the pub and the number of times they requested wine, Jim decided to expand the wine offerings in their pub. The problem was that neither Jim nor his father had much experience with wine, and they had a young and rather inexperienced wait staff who were also unfamiliar with wine. Consequently, challenges with the category arose. The case examines a fundamental question for any business; whether to grow into new and unfamiliar product categories in order to meet changes in customer preferences or to continue with the existing core competencies?

The gamma CUSUM chart method for online customer churn prediction

Customer churn in online firms is difficult to manage because customers are so fickle. The ability to detect churn in the early stage is something every online firm would wish to achieve. It represents both a potential revenue source and a cost-saving benefit. Churn prediction models attempt to organize customer behaviors, transactions and demographics to reduce the possibility of churn within a given time. However, most current methods depend on high-dimensionally static data analysis and the model parameters are estimated based on the massively customers. A dynamic and customized prediction model at the individual level cannot be achieved. This study proposes a novel mechanism based on the gamma CUSUM chart in which only inter-arrival time (IAT) and recency need to be collected, so that the customized parameters can be estimated for the purpose of individual monitoring. The data in this study are from an online dating website in Taiwan. The gamma CUSUM chart is compared with the exponential CUSUM chart of Gan (1994), CQC-v of Xie et al. (2002) and CQC of Chan et al. (2000). The results show that the accuracy rate (ACC) for a gamma CUSUM chart is 5.2% higher and the average time to signal (ATS) is about two days longer than required for the best CQC-v.

Customer's Adoption for Technology-Enabled Delivery Channels in Selected Public Sector Banks

<p><strong>Purpose</strong>–The purpose of this paper is to investigate customer’s adoption for technology-enabled delivery channels such as Automated Teller Machines (ATMs), Internet banking, Tele-banking, mobile banking and branch lobby kiosks of selected Public Sector Banks (PSBs). In addition, the study consists of the customer’s willingness for adopting banks delivery channels and customer demographics influence on delivery channels in specific for Mumbai city (India).</p><p><strong>Design/methodology/approach</strong>–For this study, structured questionnaire was administered to collect the primary data and random sampling method was adopted. The paper also presents a multi-year research effort on e-banking in delivery channels and suggests strategies to enhance the channelization of banking products and services through usage of delivery channels.</p><p><strong>Findings</strong>–The findings reveal that the customer’s willingness for adoption of various technology-enabled delivery channels is lower than the banks’ acceptable level. The usage of technology-enabled delivery channels such as Automated Teller Machines (ATMs) and Internet banking is high in Mumbai. The results also show that the usage of mobile banking and branch lobby kiosks is very low. Most of respondents are using Internet banking for the purpose of fund transfer and account information. ATMs service is highly used among 36-45 years of age groups. Promoting awareness about benefit of technology-enabled delivery channels is of utmost important to increase usage of technology-enabled delivery channels.</p><p><strong>Practical implications/limitations</strong>–The paper presents the opportunity for bank marketers to adapt to market orientated approach. They can consider customers usage pattern to increase the effectiveness of delivery channels. The results suggest that banks strategic and tactical activities require improvement in order to become more customer-focused and market-oriented. Furthermore, the scope of the study was selected PSBs’ customers residing in Mumbai city (India).</p><strong>Originality/value</strong>–Previous studies that sought adoption of innovative delivery channels lack concern to user’s inclination to technology-enabled delivery channels. This paper makes a valuable contribution in the field of marketing strategy of banks, and evaluate to what extent consumers are ready to accept and use the products or the services introduced.

Does Consumer Gender Influence The Relationship Between Consumer Loyalty And Its Antecedents?

A retailer can improve consumer loyalty to a store by identifying and implementing a suitable marketing strategy, which must start with proper understanding of the factors that influence shoppers choice behavior. Several empirical studies on buying behavior have pointed out that customer demographics may be related to store loyalty. Regarding gender, even if this variable is often perceived as a main predictor of differential outcomes in social psychology literature, it is not yet clear how these differences impact customer loyalty and the relationship between consumer loyalty and its antecedents. The findings of this study demonstrate that women are more loyal to store than men. In addition to this, it can be noted that gender does not moderate any of the relationships between loyalty and its antecedents.

Changes in awareness and use of calorie information after mandatory menu labeling in restaurants in King County, Washington.

We examined population-level impact on customer awareness and use and explored potential disparities in outcomes regarding the King County, Washington, regulation requiring chain restaurants to provide calorie information. We analyzed 2008 to 2010 Behavioral Risk Factor Surveillance System data from 3132 English-speaking King County residents aged 18 years and older who reported eating at a regulated chain. We used regression models to assess changes in calorie information awareness and use from prepolicy to postpolicy implementation by customer demographics, health status, and restaurant type. Calorie information awareness and use increased significantly from 2008 to 2010. Unadjusted analyses indicated that the proportion who saw and used calorie information tripled, from 8.1% to 24.8%. Fully adjusted analyses confirmed significant increases. After policy implementation, White, higher income, and obese respondents had greater odds of seeing calorie information. Women, higher income groups, and those eating at a fast-food versus a sit-down chain restaurant were more likely to use this information. Significant increases in calorie information awareness and use following regulation support the population-wide value of this policy. However, improvements varied across race, income, and gender.

The Relationship Between Customer Demographics and Brand Loyalty in the Indian Telecom Sector

Customer loyalty is vital in any relationship marketing effort. With little or no product and service differentiation in the telecom sector, retaining the loyalty of customers is a big challenge. Service providers are investing substantial amounts in a variety of CRM strategies. While on one hand customer loyalty is a function of good products and services, resulting in increased levels of satisfaction, on the other hand customers' social and demographic profile plays a key role in determining a customer's loyalty to his service provider. Four types of loyalty measures were categorized and relationships with the demographic variables studied. This paper explores whether customer loyalty and demographic factors are linked in the telecom sector and to what extent. The findings and interpretation are similar to what other researchers have arrived at in the past, in that there is no significant relationship between demographic factors and loyalty. This study will have a huge impact on CRM investments in the telecom sector and will make service providers rethink their customer loyalty strategies.

A Study to Explore Relationships Between Customer Demographics and Brand Loyalty in The Indian Telecom Sector

Customer loyalty is vital in any relationship marketing effort. With little or no product and service differentiation in the telecom sector, retaining the loyalty of customers is a big challenge. Service providers are investing substantial amounts in a variety of CRM strategies. While on one hand customer loyalty is a function of good products and services, resulting in increased levels of satisfaction, on the other hand customers' social and demographic profile plays a key role in determining a customer's loyalty to his service provider. Four types of loyalty measures were categorized and relationships with the demographic variables studied. This paper explores whether customer loyalty and demographic factors are linked in the telecom sector and to what extent. The findings and interpretation are similar to what other researchers have arrived at in the past, in that there is no significant relationship between demographic factors and loyalty. This study will have a huge impact on CRM investments in the telecom sector and will make service providers rethink their customer loyalty strategies.

A multi-theoretical kernel-based approach to social network-based recommendation

Recommender systems are a critical component of e-commerce websites. The rapid development of online social networking services provides an opportunity to explore social networks together with information used in traditional recommender systems, such as customer demographics, product characteristics, and transactions. It also provides more applications for recommender systems. To tackle this social network-based recommendation problem, previous studies generally built trust models in light of the social influence theory. This study inspects a spectrum of social network theories to systematically model the multiple facets of a social network and infer user preferences. In order to effectively make use of these heterogonous theories, we take a kernel-based machine learning paradigm, design and select kernels describing individual similarities according to social network theories, and employ a non-linear multiple kernel learning algorithm to combine the kernels into a unified model. This design also enables us to consider multiple theories' interactions in assessing individual behaviors. We evaluate our proposed approach on a real-world movie review data set. The experiments show that our approach provides more accurate recommendations than trust-based methods and the collaborative filtering approach. Further analysis shows that kernels derived from contagion theory and homophily theory contribute a larger portion of the model.

A national, cross-sectional survey of children's hospital-based safety resource centres

ObjectiveTo describe the location, staffing, clientele, safety product disbursement patterns, education provided and sustainability of safety resource centres (SRCs) in US children's hospitals.MethodsA cross-sectional survey was distributed to children's hospital-based...

Analysis of Various Multiobjective Genetic Approaches in Association Rule Mining

mining is used now days by companies with a strong consumer focus. It enables these companies to know the relationships among internal factors such as, product positioning, price or staff skills, and external factors such as indicators, economic, competition, and customer demographics. The overall aim of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. In this paper, the multi-objective genetic approach for the result Comparison of Pittsburgh and Michigan approach using multi-objective genetic algorithm has been proposed, and it is shown that using Pittsburgh approach is much better than the Michigan approach. KeywordsPittsburgh, Multi-objective, Genetic Algorithm.

Comprehensive framework for internet banking adoption: an empirical analysis in the Indian context

The study presents an integrated framework to analyse factors influencing consumer's acceptance of online banking services and tests its validity in the Indian context. The framework draws from two basic models most widely used in literature namely the technology acceptance model TAM and the technology readiness TR model. The results validate the basic TAM hypothesis that the intention to use internet banking is predicted by the two factors of perceived usefulness and perceived ease of using online banking technology. Age, gender and TR profiles moderate the relationship between the two factors and the behavioural intention to use internet banking. Trust in the bank was found to be another key factor driving a customer's intention. Knowledge of the customer demographics and TR profiles and how they influence his acceptance of internet banking can enable banks to understand their customers better and design tailor made marketing efforts towards activation.

An analysis of the antecedents of loyalty and the moderating role of customer demographics in an emerging mobile phone industry

Purpose – The purpose of this paper is to investigate how various antecedents influence customer loyalty in the mobile phone industry and how customer demographic variables moderate such relationships. A comprehensive model is proposed and tested empirically that features six antecedents identified in recent industry literature – customer satisfaction, perceived service quality, value, switching costs, trust, and corporate image – and common demographic variables. Design/methodology/approach – Data were collected using a field questionnaire survey of mobile phone users in Pakistan. Structural equation modeling (SEM) and multi-group SEM evaluate direct and moderating effects. Findings – Findings suggest that of six antecedents, customer satisfaction, perceived switching costs, service quality, and perceived value have positive and significant relationships with customer loyalty. Among the demographic variables, only income and area of residence moderate the relationships between customer loyalty and the antecedents. Research limitations/implications – The research was conducted in an Asian country where – due to recent liberalization – the telecommunications industry is emerging. The cultural and socio-economic diversity in Asia limits generalization of findings. Practical implications – Resource allocation that promotes customer loyalty in the mobile phone industry and improves customer satisfaction, perceived service quality, value, and switching costs can be optimized by implementing different measures for demographic groups. Policies should require mobile phone operators to invest more in rural areas to enhance and expand services. Originality/value – This study contributes to the literature by offering a comprehensive model that includes the most important antecedents of customer loyalty and customer demographics in the mobile phone industry. The model is validated empirically in the context of emerging Asian economies with new field data sourced from Pakistan.