Customer Attributes Research Articles

Understanding the attributes of digital wallet customers: Segmentation based on perceived risk during the Covid-19 pandemic

This research emphasizes the importance of digital wallet customer segmentation, mainly based on customer risk perceptions during the Covid-19 pandemic. The fundamental contribution of the study was to explain the concept of perceived risk in a digital wallet, also to confirm risk factors in digital wallets, and identify segments based on perceived risk factors. The respondents are 270 digital wallet users of OVO, Gopay, and Dana obtained in Surabaya, Indonesia, during the Covid-19 pandemic, which was taken using the purposive sampling technique. The multiple analysis data were carried out using factor analysis, cluster analysis, and difference test techniques. An essential finding of this study shows that perceived risk factors consist of security, financial, social, and operational risks. There are three segments based on the perceived risk: low-risk, medium-risk, and high-risk. Each segment has different characteristics and managerial implications.

Online Platform Customer Shopping Repurchase Behavior Analysis

With the rapid development of the world economy and the progress of modern science and technology, e-commerce has gradually spread to the public. For the online shopping platform, the number of online stores has increased rapidly, especially so in recent years. Mastering the rules of customers’ shopping behavior will help the stores to stand out amidst such a fiercely competitive environment. Taking the cosmetics industry in online shopping as an example, this paper studies the purchase behavior of online platform customers. Through the analysis of order data, it is found that the number of customers’ repurchase times and the corresponding number of people conform to the law of power-law distribution. On this basis, the customer attributes of repurchase behavior are analyzed and demonstrated, and the influences of different factors, such as region, postage, and usage of clients, on the customer repurchase rate and the relationship between the number of orders and the number of days between repurchase are revealed. The analysis results can provide better sustainable operation decision support for online platform operators and improve the overall repurchase rate and benefits of stores.

Automated, human, or semi-automated service in restaurants? An investigation of technology-enabled service designs and customer attribution

Self-serving bias tends to lead customers to attribute ideal outcomes to themselves while blaming external factors for non-ideal outcomes. This attribution process complicates the current service configuration owing to service increasingly incorporating automated or semi-automated processes where the traditional human services are replaced or reduced. This research provides insights into how such changing service dynamics may impact restaurant customers' attribution behavior. By utilizing a 2 × 3 between-subject scenario-based experimental design, this study shows that restaurant service types (automated, employee, and semi-automated services) and service outcomes (with and without service failure) influence consumer attribution and subsequent service satisfaction. This study allows a better understanding of how customers perceive a service failure and the absence of service failure when such services interface with technology-enabled hospitality configurations.

Come fly with me: exploring the private aviation customer experience (PAX)

PurposeThis study aims to address the need to empirically investigate the luxury customer service experiences of the ultra-high-net-worth individual (UHNWI) segment by conducting and analyzing interviews with 20 clients flying private jets. The results lead to a conceptualization of the UHNW private aviation customer experience.Design/methodology/approachThis study applied a three-step method to explore the meaning and domain of the UHNWI luxury service experience. First, the perception and corresponding attributes of customers’ experiences using private aviation services were examined through 20 in-depth interviews and by using the soft laddering technique. Second, this study coded and, subsequently, purified the data by means of a systematic comparison approach and hierarchical coding. Third, a panel of judges, using the emerging consensus technique, scrutinized and validated the emerging dimensions.FindingsThe analysis reveals the customer experience (CX) and motivations differ significantly between business and leisure use, moving from a functional toward an experiential value focus. The findings emphasize the lack of social value for the UHNWI CX and introduce time as a new value dimension.Research limitations/implicationsThis study provides multiple contributions to the customer experience, luxury and luxury services literature. This study enhances scholarly understandings of the holistic UHNWI CX in the context of an absolute luxury offering, thus providing a needed conceptualization of an underresearched customer segment, namely, the UHNWI. It delivers insights on the different motivations and experience UHNWI are seeking for according to the context. This study proposes a new luxury value dimension: time.Practical implicationsThis study highlights multiple opportunities for UHNWI customer experience improvement. The findings reveal that different clients are looking for different experiences in terms of business versus leisure use. The key drivers and expectations shift from functional (price/availability/flexibility) to experiential factors (comfort/onboard experience/relationship with crew and pilot). Communication, marketing and CX management strategies and tactics need to emphasize this important distinction regarding what drives client behavior in the private aviation setting.Originality/valueThe contribution of this paper is threefold. First, it defines UHNWI characteristics and overall experiences using the unique über-service of private aviation, thus advancing scholarly understanding of both the luxury customer and the luxury customer service experience beyond the proposed traditional drivers of luxury consumption. Second, this study expands the conceptual foundation for the UHNWI “über-luxury” service experience, which, given the importance of the UHNWI segment, is important. Third, this study contributes to theoretical knowledge by extending customer value perception in the luxury context by introducing the luxury value dimension of time. This study concludes with a discussion of its findings’ implications for luxury research and practice, providing a future research agenda with regard to UHNW.

Packaging development of dehydrated strawberry using quality function deployment for e-commerce

Dehydrated strawberry is product development from strawberry fresh fruit to improve, increase the shelf-life and value of the product. During the Covid-19 pandemic, shopping lifestyle has changed gradually into online buying through e-commerce that was growth significantly, it must be followed by producer to adapt and adopt the situation especially for purchasing decisions, while customers tend to choose products based on the packaging appearance. This study aimed to determine attributes of the packaging and technical needs for producer selling preparation of dehydrated strawberry in e-commerce based on customer needs. The method in this study that has proven effective in fulfilling customer needs is Quality Function Deployment (QFD) in product planning phase. QFD analysis begins with filtering Voice of Customer (VoC) using open questionnaire then at the stage of customer importance level and product performance using closed questionnaire, then compiled into attributes of customer needs. Technical requirements were brainstormed using discussion with local sellers on e-commerce. Two attributes with the highest priority to be realized is product information on the packaging is easy to read and understand and product-related information fully listed on the outer product packaging and the highest priority for the technical needs is addition of secondary packaging.

The Impact of Hotel Customer Experience on Customer Satisfaction through Online Reviews

With the growing popularity of the internet, customers can easily share their experiences and information in online reviews. Consumers recognize online reviews as a useful source of information prior to consumption, and many online reviews influence consumer purchasing decisions. Understanding the customer experience in online reviews is thus necessary to maintain customer satisfaction and repurchase intention for the sustainable development of the hotel business. This study assessed the fundamental selection attributes of customers from online reviews reflecting the hotel customer experience, and investigated their association with customer satisfaction. A total of 8229 reviews were collected from Google travel websites from December 2019 to July 2021. Text mining and semantic network analysis were adopted for big data analysis. Factor and regression analyses were then used for quantitative analysis. Based on linear regression analysis, the Service and Dining factors significantly affected customer satisfaction. Service is a critical selection attribute for customers, and the provision of more particular services is necessary, especially after COVID-19. These results indicate that understanding online reviews can provide theoretical and practical implications for developing sustainable strategies for the hotel industry.

Investigating Online Purchase Intension Antecedents: A Study of e-Tailing Experiences

In today’s era the internet and smartphone has changed the way of communication and doing the business. The rapid growth of online shopping facilitates new opportunities to do business. To grab the opportunities and develop strategies to deal with the possible challenges in the Indian e–commerce market, the e-tailers should have the understanding about the e– commerce market and the factors affecting the online shopping behaviour of consumers. In this context, this study aims at investigating the attributes affecting the online shopping behaviour in the state of Odisha. It also examines the perception towards the various online shopping attributes like website attributes and customer attributes. This study is based on empirical survey, with the help of structured questionnaire through both online and offline modes. Data analysis has been done using SPSS software. The findings of this study suggests “website attributes” (comprising interactivity/ connectivity, privacy and safety, website atmospherics, trust, website usability, order fulfilment and customer support) and “customer attributes” (including telepresence, perceived risks, online shopping attitude, website reputation, perceived control, perceived skills, perceived self-efficacy and ease of use) have a significant relationship with customer experience. Demographic variables like income, age and gender were found to have significant impact on the medium of online shopping used.

공연예술 상품 소비자들의 선택속성이 구매만족과 고객충성도에 미치는 영향

The purpose of this study was to accurately grasp the service attributes provided in art performance halls. The analyzed service attributes were conducted to develop a service marketing strategy for market and customer satisfaction. The tool of the study is a questionnaire. In order to achieve the purpose of the study, measurement tools for each concept used in previous studies were secured, and then reconstructed and used to suit the purpose of the study. The attributes of customers

Selection of Product recommendation using EDAS method

Product recommendations, e-commerce personalization Part of the strategy is the customer Attributes, browsing behavior or contextual context based on data such as web page, application or products change to a user via email Categorize by category—offers a personalized shopping experience. The top 4 trusted sources for referrals are a close friend, family member, brand advocate, and product Expert. peer-to-peer rather than celebrity endorsement; Peer referrals 20 times more valuable. 49% make referrals because they want to help people. Estimation Based on the distance from the mean solution (EDAS). A new and efficient MCDM method. In this method alternatives are selected from the average solution Determined based on their distance. Alternative: Picture (C1), Zoom (C2), Battery (C3), and Memory (C4). Evaluation Preference: Camera (A1), Camera (A2), Camera (A3), Camera (A4), Camera (A5), Camera (A6). From the result it is seen that Camera (A5) and is got the first rank whereas is the Camera (A3) got is having the lowest rank. The value of the dataset for Product recommendations in EDAS method shows that it results in Camera (A5) and top ranking.

A Novel Blockchain and Bi-Linear Polynomial-Based QCP-ABE Framework for Privacy and Security over the Complex Cloud Data.

As a result of the limited resources available in IoT local devices, the large scale cloud consumer’s data that are produced by IoT related machines are contracted out to the cloud. Cloud computing is unreliable, using it can compromise user privacy, and data may be leaked. Because cloud-data and grid infrastructure are both growing exponentially, there is an urgent need to explore computational sources and cloud large-data protection. Numerous cloud service categories are assimilated into numerous fields, such as defense systems and pharmaceutical databases, to compute information space and allocation of resources. Attribute Based Encryption (ABE) is a sophisticated approach which can permit employees to specify a higher level of security for data stored in cloud storage facilities. Numerous obsolete ABE techniques are practical when applied to small data sets to generate cryptograms with restricted computational properties; their properties are used to generate the key, encrypt it, and decrypt it. To address the current concerns, a dynamic non-linear polynomial chaotic quantum hash technique on top of secure block chain model can be used for enhancing cloud data security while maintaining user privacy. In the proposed method, customer attributes are guaranteed by using a dynamic non- polynomial chaotic map function for the key initialization, encryption, and decryption. In the proposed model, both organized and unorganized massive clinical data are considered to be inputs for reliable corroboration and encoding. Compared to existing models, the real-time simulation results demonstrate that the stated standard is more precise than 90% in terms of bit change and more precise than 95% in terms of dynamic key generation, encipherment, and decipherment time.

Customer attribution toward corporate social responsibility: the importance of social justice in COVID-19 donation

PurposeLiterature on corporate social responsibility (CSR) has given much attention to the impact of CSR initiatives on business performance. However, managing customers’ attributions to the company’s social activities are also needed. This study aims to extend the existing knowledge by examining the role of social justice as a moderating variable in the relationships among corporate brand image, CSR motive, corporate brand trust and loyalty.Design/methodology/approachThe research data were collected from a sample of 710 respondents in Indonesia through an online survey. The variables used in this study’s questionnaire were adapted from previous studies. The focus of the survey was a COVID-19-related social activity conducted by the biggest private telecommunication company in Indonesia. Structural equation modeling was used to analyze the data and test the hypotheses.FindingsThe results showed that social justice moderated the relationship between corporate brand image and CSR motive. Also, social justice that revealed fairness in social life could influence how customers respond on company social activities and thus create corporate brand trust and loyalty.Research limitations/implicationsThis study focused on only one company and one type of CSR activity (i.e. philanthropy) that might limit its generalizability. Future studies can focus on other types of CSR activities from various companies and industries.Practical implicationsIn designing their social activities, companies must consider the importance of social justice. Companies need to address customers’ concerns toward social and society problems, especially to overcome social, environmental or health problems. Hereinafter, companies must design CSR activities that establish and accentuate their value motives by creating communication through media and public relations activities to symbolize their high concern for social problems or disasters.Originality/valueMost previous studies consider the outcome of social activities and their impact on business performance. This study focuses on the impact of corporate brand image and social justice (as an individual characteristics) on CSR (social activities) and how it can further enhance business performance (corporate brand trust, corporate brand image, loyalty) and enrich CSR research in emerging economies.

Customers’ relationship maintenance and loyalty intentions after a brand transgression: a moderated mediation approach

ABSTRACT The study seeks to establish the role of relationship marketing orientation of banks and customer attributions of the transgression in customers’ continuance intentions and loyalty towards the bank after a brand transgression. A moderated mediation model showing relationships between relationship marketing orientation, customer commitment and customer loyalty intentions after a real-life transgression was formulated. In a survey conducted among 340 bank customers in India, results suggest positive and significant roles of relationship marketing orientation on relationship continuation intentions and customer loyalty, after a transgression. The strengths of these intentions varied according to the customers’ perceptions of the bank’s active role in the transgression. However, contrary to expectations, customers who perceived a more active role of the bank in the transgression, showed stronger intentions of continuing their relationship with the bank.

Contribution of green manufacturing for realizing business performance in Indian small and medium scale organizations (SME’s)

PurposeThe current manuscript is focused on evaluating the capabilities of green practices that affect various business performance (BP) parameters of small and medium scale Indian manufacturing enterprises (SME’s). This study aims to obtain multiple significant factors that influence the implementation of green practices.Design/methodology/approachThe manuscript focuses on statistical testing of responses obtained from 168 Indian SMEs to determine the relationship between input parameters and BP parameters. This paper starts with deploying tests such as Cronbach alpha and inter-item covariance test to obtain confidence in data collected, followed by various statistical tests such as Pearson correlation, multiple regression, canonical correlation to extract various significant factors the study. Further Games-Howell post hoc test is deployed to evaluate the significant improvements in BP gained over a reasonable duration of time. Finally, a discriminant validity test is used to find out the success or failure of the organizations that participated in the survey.FindingsThis research contributes to the holistic effect of green manufacturing (GM) toward gaining improvements in terms of different BP parameters taken for the study. It has been found that various input factors such as customer attributes, adoption of new technology, social pressure and government pressure are the main parameters for GM implementation. Further, it is observed that those at the maturity phase of GM implementation are reaping higher benefits than the organizations at the transition and stability phase.Originality/valueThe current study has been accomplished in Indian SME manufacturing organizations to investigate the effects of GM implementation in the organization. Although research findings imply the effective use of green practices within the organization to reap BP parameters and improve the market’s competitive image, the study cannot be generalized and can be used as an insight for both academicians and end-users in understanding the overall achievements of GM.

The Analyze of Relationship between Revenue and Customer Payment Methods in Small Medium Enterprise Based on Clustering K-Means

Business capital and revenue are not only the decisive of the health of SMEs but also they must be balanced. In general, customers find their benefit from the flexible payment methods while on the other hand the SMEs should get their benefit too. So that, it needs to be studied whether it is necessary for SMEs to get their profit in accordance to this situation. One of the methods that suitable to be applied is by applying customer groupings based on revenue and payment namely the K-means clustering method since it can raise several groups that have not been known before. This information is useful for SMEs to be utilized based on their needs. Data in this study were gathered from customer attributes, number of transactions, and payment methods. The number of centroids was 3. The grouping results were stopped at the 5th iteration. The finding showed that the ratio value of the 4th iteration and the 5th iteration having the same ratio value, 0.07393. From the results of the iterations can be found; first, based on the customers’ number, the groups can be classified into three C1(18%), C2 (45%), C3 (36%). Second, based on the average number of transactions, post-paid payments was in the first rank (12.7 / week). From the results, it can be analyzed that this situation is burdensome for SMEs because the more the number of transactions, the more investment must be prepared for accounts receivable.

Influencing Factors of Facial Spa Treatment on Visit Intention: An Importance-Performance Matrix Analysis (IPMA) Approach

Nowadays, grooming is considered an essential part of life to maintaining and up keeping a healthy and hygienic outlook which plays a key role in social bonding. As it turns out, the desire to looking good has spawned a wide range of beauty products causing the beauty industry to thrive and grow at a rapid rate. In other words the Malaysian Beauty Salon Markets have become big business today, driven by a rising population, disposable incomes, urbanisation and increasing influence of western culture to look good and to feel good. The beauty market is valued at USD 119.24 million and is expected to grow at a CAGR of 5.23% in the next five years, to USD 153.86 million in 2015. As a result of a highly fragmented in this market, the need for differentiation from other salons is impendency for this industry. This research aims to study the different attributes of customer's concerns and reveals the final factors that generate customer intention to visit facial spa treatment centres in Malaysia. The effort is devoted to identifying those dimensions of services provided in facial spa treatment centres for instance, atmospheric, service quality, price, brand image and location which aid to build up a greater relationship with their patrons. Data is collected via questionnaires distribution from the target population of the female with the age range from 16-63 years old. A sample size of 308 was studied and data analysis involving Structural Equation Modeling SmartPLS version 3.0 software were used. Service quality reached the conclusion as the strongest predictor in influencing customer intention to visit facial spa treatment centres, followed by the factors of price and brand image. Further to that, an Importance-Performance matrix analysis was conducted in order to identify factors that need to be given priority for spa owners in Malaysia. These findings made contributions beyond the high context services for instance beauty salons, massage salons, hair salons, nail salons, financial consulting and medical care with the matching services characteristics.

Predicting pedestrian flow along city streets: A comparison of route choice estimation approaches in downtown San Francisco

Street attributes are thought to play an important role in influencing pedestrian route choices. Faced with alternatives, pedestrians have been observed to choose faster, safer, more comfortable, more interesting, or more beautiful routes. Literature on pedestrian route choice has provided methods for assessing the likelihood of such options using discrete choice models. However, route choice estimation, which is data intensive and computationally challenging, remains infrequently deployed in planning mobility analysis practice. Even when coefficients from previous studies are available, operationalizing them in foot-traffic predictions has been rare due to uncertainty involved in the transferability of behavioral effects from one context to another, as well as computational challenges of predicting route choice with custom attributes. This paper explores a simpler method of route choice prediction, implemented in the Urban Network Analysis toolbox, which assigns probabilities to available route options based on distance alone. We compare the accuracy of distance-weighted approaches to the more detailed utility-weighted approach using a large dataset of observed GPS pedestrian traces that include numerous trips between same intersections pairs in downtown San Francisco as a benchmark. Even though a utility-weighted model matches observed pedestrian flows most accurately, a distance-weighted model is only marginally inferior, on average. However, shortest-distance and highest-utility route predictions are both significantly inferior to the utility-weighted and distance-weighted sample-enumeration methods. Our findings suggest that simplified assumptions can be used to predict pedestrian flow in practice with existing software, opening pedestrian flow predictions to a wider range of planning and transportation applications.

Validation of green manufacturing implementation practices in small and medium-scale organisations

The current paper is focused to investigate and select various significant parameters that effect implementation of green manufacturing in Indian small and medium scale manufacturing organisations. In this study, Structural Equation Modelling (SEM) technique is employed to validate the interrelation between various Green Manufacturing (GM) input parameters and their effect on GM implementation. In this study, Confirmatory Factor Analysis (CFA) approach is used to generate the impressive SEM_GM model using AMOS 20 (Analysis of Moment Structures) software. The data have been collected from different small and medium-scale manufacturing organisations implementing GM with the help of well-framed GM questionnaire for the generation of SEM_GM model. Structural Equation Modelling of various parameters effecting green manufacturing implementation like Peer Government Pressure (PGP), Peer Social Pressure (PSP), Customer's Attributes (CA), Green Supply Chain Management (GSCM) and Adoption of new/supportive technology (ANT) for enhancing business performance has been performed. The constructed model named SEM_GM adjusted according to the modification indices obtained from the software and model fitness values are compared before and after modification. The research concludes at PGP, CA, GSCM and ANT effecting GMI in Indian small and medium scale manufacturing organisations whereas PSP not positively impacting implementation.

A Literature Review of Data Mining Techniques for Enhancing Digital Customer Engagement

The evolution of the customer engagement concept had a positive impact on how business and customers interact. The term digital customer engagement emerged to empower such interaction via encouraging customers to use digital channels. Data mining techniques can help in identifying patterns, generating insights, and making predictions for a massive amount of data. The purpose of this paper is to explore the current literature on data mining techniques to enhance digital customer engagement and review the impact of data mining on analyzing customer's attributes and its key performance indicators influenced by digital customer engagement and affecting business success. The scope of the review encompasses the state of the art of scientific methodologies and models applied to identify customers with the highest potential towards digital engagement. A critical analysis also identified gaps in the literature. This study is the first to explicitly consider data mining techniques for enhancing digital customer engagement with a comprehensive analysis of customer's attributes in different domains.

IPA를 활용한 커피전문점 선택속성에 관한 연구: 중국내 한국 커피 브랜드 중심

The purpose of this study is to analyze the attributes of Chinese coffee shop customer using IPA. The data was collected in Guangzhou, Shanghai, China, between Sep. 20, 2018 and Oct. 10, 2018. 397 samples were used for final analysis by SPSS 18.0. The results of the analysis and evaluation are as follows. First, the questions about consistent taste, amount of coffee, the variety of the coffee menu, the diversity of other menus, and brand awareness can be seen to have high satisfaction compared to the importance, and the rest of the other questions can be judged to be generally dissatisfied because they all display the value of the positive (+). Second, based on the results of IPA analysis, most of the attributes about coffee taste, physical environment and brand are in the grid 1 known as

Robots or frontline employees? Exploring customers’ attributions of responsibility and stability after service failure or success

PurposeService robots are taking over the organizational frontline. Despite a recent surge in studies on this topic, extant works are predominantly conceptual in nature. The purpose of this paper is to provide valuable empirical insights by building on the attribution theory.Design/methodology/approachTwo vignette-based experimental studies were employed. Data were collected from US respondents who were randomly assigned to scenarios focusing on a hotel’s reception service and restaurant’s waiter service.FindingsResults indicate that respondents make stronger attributions of responsibility for the service performance toward humans than toward robots, especially when a service failure occurs. Customers thus attribute responsibility to the firm rather than the frontline robot. Interestingly, the perceived stability of the performance is greater when the service is conducted by a robot than by an employee. This implies that customers expect employees to shape up after a poor service encounter but expect little improvement in robots’ performance over time.Practical implicationsRobots are perceived to be more representative of a firm than employees. To avoid harmful customer attributions, service providers should clearly communicate to customers that frontline robots pack sophisticated analytical, rather than simple mechanical, artificial intelligence technology that explicitly learns from service failures.Originality/valueCustomer responses to frontline robots have remained largely unexplored. This paper is the first to explore the attributions that customers make when they experience robots in the frontline.