Customer Approach Research Articles

Marketing mix of financial services from the customers perspective

The aim of this paper is to show tactical marketing in the 5C concept, services perception and consumer behaviour in the financial products market. Primary marketing research was based on the number of 412 respondents. The consumers were questioned about their behaviour within the topic of customer value, costs to the customer, convenience, communication and customer approach. When deciding about the selection of financial institutions and financial products as fundamental criteria are said to be costs to the customer – pricing policy, convenience – physical availability of branches and their physical evidence. Further research outputs indicate that customers tend rather to savings products and life insurances than to credit products. The costs incurred for the purchase of financial products are perceived as adequate. Direct distribution channels still play and will play important role in financial services. It seems effective to use BTL communication than massive advertising. Demands on financial institutions front-office employees have increased when regarding a quick solution of customers´ demands and acceptable soft skills. Keywords: marketing, “5C” marketing mix, financial services, primary marketing research.

A Baseline Load Estimation Approach for Residential Customer based on Load Pattern Clustering

Demand response (DR) is a key technology enabling reliable and flexible power system operation more economically and environment-friendly than conventional manners from supply side. Customer baseline load (CBL) estimation is an important issue in the implementation of DR programs for assessing the performance of DR programs and designing economic compensation mechanisms. The accurate estimation of CBL is critical to the success of DR programs because it involves the interests of multi-stakeholders including utilities and customers. Motivated by the inaccuracy of existing CBL methods, this paper proposes a residential CBL estimation approach based on load pattern (LP) clustering to improve the accuracy of CBL estimation. First, an adaptive density-based spatial clustering of applications with noise (DBSCAN) algorithm is proposed to extract typical load patterns (TLPs) of each individual customer in order to avoid the adverse effects from aggregating many dissimilar LPs together as the real TLP. Second, K-means clustering is utilized to segment residential customers into several different clusters based on the similarity of LPs. Finally, CBLs for DR participants are estimated based on the actual load of non-participants at the same cluster during DR event periods. The proposed methods are compared with some traditional methods on a smart metering dataset from Ireland. The results show that the proposed methods have a better performance on accuracy than averaging and regression methods.

Embedded DRAM-Based Memory Customization for Low-Cost FFT Processor Design

In this paper, we present embedded dynamic random access memory (eDRAM)-based memory customization techniques for low-cost fast Fourier transform (FFT) processor design. The main idea is based on the observation that the FFT processor has regular and predictable memory access patterns, and it can be efficiently exploited for memory customization using eDRAM. The memory customization approaches are applied to both of the pipelined and memory-based FFT architectures. In the pipelined architecture, the read wordline (RWL) coupling write assist and data packing schemes are employed to reduce the redundant RWL and wordline driving, respectively, in column-interleaved memory arrays. The memory address decoder is also simplified with thermometer code by exploiting the sequential access patterns. For the memory-based architecture, the modified cached-memory structure is employed in addition to the techniques used in the pipelined FFT architecture. The hardware implementation results of 2k-point FFT with a 0.11- $\mu {\mathrm{ m}}$ CMOS technology show that the proposed eDRAM-based pipelined and cached-memory FFTs achieve 26.8% and 33.2% power savings over the static RAM-based FFT design, respectively.

Corporate leverage: structural equations framework in an emerging economy

PurposeThe purpose of this paper is to investigate the financing behavior of firms in Pakistan. Previous studies have investigated corporate leverage determinants within any particular industry, such as manufacturing industry, textiles industry, etc., with varying results. This is one of the few studies that examine the determinants of leveraging attitude of firms across industrial sectors for textiles, large industries, and small industries. Thus, the study provides an insight into the general debt financing behavior in Pakistan and allows a basis for comparison of the leveraging decisions across industries.Design/methodology/approachThe study employs the structural equations methodology which captures the endogenous relationship between profitability and leverage. Thereby, eliminating bias and providing more accurate results.FindingsThe findings suggest that the leveraging decisions differ across sectors and that each industry has its own distinctive debt requirements/characteristics. The authors conclude that a singular approach taken by investors and analysts would provide inaccurate assessment of firms’ debt financing policies and strategies.Research limitations/implicationsThere is a limitation on data availability in emerging countries, and a larger sample would have provided more robust results. Therefore, the study has only taken three sector sub-divisions, and more industry categories would have provided in-depth insights into the industry-wise leveraging behavior.Practical implicationsThis is the first study to suggest that the borrowing attitude of firms differ across industries and vary due to their specific needs. This has implications for government regulators, investors, and creditors in providing a more customized approach to analyzing and meeting the external financing needs of firms.Originality/valueThis study is the first to use simultaneous equations model to eliminate bias that is prevalent in similar studies in Pakistan. The SEM captures the endogenous relationship between profitability and leverage. The research provides important information about the underlying financing behavior across industries, which has largely been ignored.

ЯПОНСКИЕ БАНКИ НА РОССИЙСКОМ РЫНКЕ

The paper focuses on entry cases of Japanese banks into Russia’s market by investigating the history of foreign entry, entry modes, and motivation for entry. By empirically examining the relevant cases, we demonstrate that the foreign entry of Japanese banks into Russia’s market was implemented in several stages starting from the 1992 and was mostly motivated by “follow the customer approach.” During the initial stages of entry, Japanese banks actively applied the “organic growth strategy” and established representative offices in Russia that were later transformed into domestic subsidiaries (Russia’s domestic juridical entities with Japanese capital participation). The paper also highlights the fact that the motivation for entry and entry modes of Japanese banks in Russia are subject to change over time. The analysis of activities of banks with Japanese capital participation of more than 50% reveals that starting from 2006, Japanese banks preferred the brownfield type of investments and acquired a few Russian banks in order to minimize costs of entry and other transaction costs. The detailed examination of the ultimate owners of banks with foreign capital participation allowed to identify the fact that Japanese banking FDI is directed to Russia via third countries such as Germany and the Netherlands. In addition, we defined the following segments of Russia’s banking market where banks with Japanese capital participation operate: support of Japanese companies and their affiliated businesses in Russia, financial services procurement to large Russian companies and banks, retail business (automobile credits), and internet-banking. Despite the fact that the activities of banks with Russian capital participation remain rather limited, recent agreements on further promotion of Japan-Russia economic cooperation leave a window of opportunity for Japanese banks to increase the scope of their activities in Russia. In fact, some banks already demonstrate growing interests to financing small and medium enterprises in Russia.

TTHLS: an HLS tool for testable hardware generation

This paper presents a new methodology to incorporate testability to Technology driven high-level synthesis, which is a customized high level synthesis approach based on the target technology. This new methodology called testable technology driven high-level synthesis, generates testable hardware from the corresponding HDL input. Testability incorporation at this higher abstraction, using this integrated approach, proves to be better in terms of area and power consumption than the conventional approaches. The experimental results for the examples considered here prove that the proposed method can reduce up to 9.38% in terms of silicon area and 1.89% in terms of power consumption.

Making Education Work: School Autonomy and Performance

The autonomy of schools is often considered to be improving school performance. However, there is some evidence that there could be conditional factors for such a relationship. This article analyzes the effect of social capital on the relationship between school autonomy and its performance. The study is based upon a new public management approach and uses PISA test data across more than 1,500 schools and multi-level modelling to answer the question. The results suggest that performance of schools is dependent on the level of social capital in the country. Autonomy of schools in countries with more social capital has a positive effect on performance, while autonomy of schools in countries with less social capital brings a negative effect for school performance. The results invite policy-makers for a more customized approach to educational reforms.

Rehabilitation Counseling: Emerging Opportunities in the 21st Century

The skillset required to be an effective rehabilitation counselor has become increasingly more complex in previous decades. To meet this demand, rehabilitation counselors (RCs) must establish requisite skills for translating empirically-based methods into clinical application. In the 21st century, there are several specific topic areas in which rehabilitation counselors should be adept. These include the use of a dual customer approach, provision of culturally responsive services to minority populations, provision of services for individuals with severe physical disabilities, familiarity with pertinent legislation at the state and federal level, and an understanding of emerging technology that can assist individuals with disabilities in the workplace. Competency in these areas must come from fieldwork or other applied opportunities, in addition to postsecondary coursework. This article will provide an in-depth look at each topic area.

Optimizing Distributed Machine Learning for Large Scale EEG Data Set

Distributed Machine Learning (DML) has gained its importance more than ever in this era of Big Data. There are a lot of challenges to scale machine learning techniques on distributed platforms. When it comes to scalability, improving the processor technology for high level computation of data is at its limit, however increasing machine nodes and distributing data along with computation looks as a viable solution. Different frameworks and platforms are available to solve DML problems. These platforms provide automated random data distribution of datasets which miss the power of user defined intelligent data partitioning based on domain knowledge. We have conducted an empirical study which uses an EEG Data Set collected through P300 Speller component of an ERP (Event Related Potential) which is widely used in BCI problems; it helps in translating the intention of subject w h i l e performing any cognitive task. EEG data contains noise due to waves generated by other activities in the brain which contaminates true P300Speller. Use of Machine Learning techniques could help in detecting errors made by P300 Speller. We are solving this classification problem by partitioning data into different chunks and preparing distributed models using Elastic CV Classifier. To present a case of optimizing distributed machine learning, we propose an intelligent user defined data partitioning approach that could impact on the accuracy of distributed machine learners on average. Our results show better average AUC as compared to average AUC obtained after applying random data partitioning which gives no control to user over data partitioning. It improves the average accuracy of distributed learner due to the domain specific intelligent partitioning by the user. Our customized approach achieves 0.66 AUC on individual sessions and 0.75 AUC on mixed sessions, whereas random / uncontrolled data distribution records 0.63 AUC.

Design of 16 Bit Vedic Multiplier Using Semi-Custom and Full Custom Approach

Design of 16 Bit Vedic Multiplier Using Semi-Custom and Full Custom Approach

Information Display in the Intensive Care Unit – Considerations for System Design and Implementation

Healthcare working environments are complex, and intensive care units (ICUs) are particularly complex due to the influx of data to the healthcare professionals who are providing continuous care to the most critically ill patients. Systems that are designed to work in these environments should take into consideration varied patient conditions, the clinical professionals who use these systems, and the features and performance requirements that will support their efforts to provide care to their patients. We suggest that developing systems that will meet these challenges requires customized design approach, including cognitive system engineering. Until recently, this work domain has been largely ignored by manufacturers of patient monitoring systems. This panel brought together two separate teams who have been using such an approach independently to design new systems for information integration and display in ICU settings. The goals of this panel discussion were to take a close look at the tools and methods that are being used for such a cognitive system engineering approach to the design processes, and to review the recommendations and concepts that are emerging from these processes from each of the two independent teams. This paper summarizes the presentations made during the panel by the two teams regarding updates of ongoing work followed by a lively discussion between panelists and the symposium participants in the audience. Each team had its unique design process that was customized to the specific target ICU, the available resources and goals. The designed systems have original features that evolve from the unique needs of the target unit, yet the designs also share some common features.

Neoliberal Ideology and College Students: Developing a Customer Orientation While in College

This longitudinal study investigates changes in the extent to which students express or reject a customer orientation towards their education from their initial summer orientation to the end of their second year in college. Fifteen of the 19 items associated with a customer orientation included in the survey (N=3885, n=1085, RR= 28%) exhibited statistically significant changes, all in ways consistent with a greater expression of a customer approach. Results also indicated that while students increasingly expressed a customer orientation, overall, they continued not to express beliefs consistent with a customer approach. Implications are discussed within the framework of neoliberal ideology.

Battery Functionality and Reactivity of a Cathode for Magnesium Ion Battery

Post lithium ion battery is highly demanding energy storage for smaller scale as stationary use to greater scale as grid storage, and vehicle use as well. Magnesium ion battery with metal magnesium as an anode has been investigated over decades because of its high theoretical capacity of magnesium (3833 mAh cm3) and relatively lower potential (0.7 V vs lithium) for naturally abundant mineral resources in “multivalent” metals with less risk on forming dendritic deposits [1]. After over a decade of finding of stable and reversible electrolyte based on Grignard agent such as APC [2], our finding of magnesium monocarborane [3] opened next door toward high energy density by its wider potential window up to 3.7 V and high current density more than 1mS cm-1, without corrosive issue which is intrinsic to conventional electrolytes containing chlorine. Although of many efforts for electrolytes and electrodes, the battery system has lack of cathode capable of providing high potential and / or capacity with stable performance over numbers of cycles in charge and discharge, to takeover Li ion battery. Recently some challenges proved custom approach for magnesium ion effective to certain extent; eg. C60 [4] works as a mimic of cluster aspect of highly reversible Chevrel Mo6S8, and spinel Ti2S4 [5] presents the design of host framework with “soft” anion and ionic path. In this study we approach to new insights into active materials by means of charge transfer. Interfacial analysis such as electrochemical impedance, XPS, etc., to the most established cathode, Chevrel phase Mo6S8 [1] in contact with MMC electrolyte gives some key factors of highly reversible cathode. Besides, our new approach for a cathode active material and its battery performance will be introduced for the next step of the reaction design.

Corporate Leverage: Structural Equations Framework in an Emerging Economy

Purpose The purpose of this paper is to investigate the financing behavior of firms in Pakistan. Previous studies have investigated corporate leverage determinants within any particular industry, such as manufacturing industry, textiles industry, etc., with varying results. This is one of the few studies that examine the determinants of leveraging attitude of firms across industrial sectors for textiles, large industries, and small industries. Thus, the study provides an insight into the general debt financing behavior in Pakistan and allows a basis for comparison of the leveraging decisions across industries. Design/methodology/approach The study employs the structural equations methodology which captures the endogenous relationship between profitability and leverage. Thereby, eliminating bias and providing more accurate results. Findings The findings suggest that the leveraging decisions differ across sectors and that each industry has its own distinctive debt requirements/characteristics. The authors conclude that a singular approach taken by investors and analysts would provide inaccurate assessment of firms’ debt financing policies and strategies. Research limitations/implications There is a limitation on data availability in emerging countries, and a larger sample would have provided more robust results. Therefore, the study has only taken three sector sub-divisions, and more industry categories would have provided in-depth insights into the industry-wise leveraging behavior. Practical implications This is the first study to suggest that the borrowing attitude of firms differ across industries and vary due to their specific needs. This has implications for government regulators, investors, and creditors in providing a more customized approach to analyzing and meeting the external financing needs of firms. Originality/value This study is the first to use simultaneous equations model to eliminate bias that is prevalent in similar studies in Pakistan. The SEM captures the endogenous relationship between profitability and leverage. The research provides important information about the underlying financing behavior across industries, which has largely been ignored.

Microbiome Helper: a Custom and Streamlined Workflow for Microbiome Research.

Sequence-based approaches to study microbiomes, such as 16S rRNA gene sequencing and metagenomics, are uncovering associations between microbial taxa and a myriad of factors. A drawback of these approaches is that the necessary sequencing library preparation and bioinformatic analyses are complicated and continuously changing, which can be a barrier for researchers new to the field. We present three essential components to conducting a microbiome experiment from start to finish: first, a simplified and step-by-step custom gene sequencing protocol that requires limited lab equipment, is cost-effective, and has been thoroughly tested and utilized on various sample types; second, a series of scripts to integrate various commonly used bioinformatic tools that is available as a standalone installation or as a single downloadable virtual image; and third, a set of bioinformatic workflows and tutorials to provide step-by-step guidance and education for those new to the microbiome field. This resource will provide the foundations for those newly entering the microbiome field and will provide much-needed guidance and best practices to ensure that quality microbiome research is undertaken. All protocols, scripts, workflows, tutorials, and virtual images are freely available through the Microbiome Helper website (https://github.com/mlangill/microbiome_helper/wiki). IMPORTANCE As the microbiome field continues to grow, a multitude of researchers are learning how to conduct proper microbiome experiments. We outline here a streamlined and custom approach to processing samples from detailed sequencing library construction to step-by-step bioinformatic standard operating procedures. This allows for rapid and reliable microbiome analysis, allowing researchers to focus more on their experiment design and results. Our sequencing protocols, bioinformatic tutorials, and bundled software are freely available through Microbiome Helper. As the microbiome research field continues to evolve, Microbiome Helper will be updated with new protocols, scripts, and training materials.

What’s the “Thing” in Internet of Things in Grocery Shopping? A Customer Approach

The Internet of Things (IoT) technology presents an opportunity for retail groceries to develop an infrastructure that makes physical things such as mobile phone, shopping basket, store shelves, digital display, and, even the product itself smart, allowing real-time interaction with customers both in the physical store and in the virtual store. The aim of this study is to expand understanding of how IoT can create value in the retail grocery choice situation. To investigate the impact of IoT-related information on consumer choice in a shopping situation, we arranged a conjoint experiment in which participants (n = 61) purchased fresh salmon in a grocery store. The results (Pearson´s r = 0.939, p = 0.000) show that relative to static information about price, expiry date, quality, and offers given, the real-time information was the most salient stimulus when choosing fresh salmon. Moreover, quality ratings by other customers were the most salient stimuli among real-time information, followed by an offer based on a product in the shopping cart, real-time expiry date, and real-time price. These findings contribute both to researchers and managers within grocery retailing who want to understand how IoT can be used in a way that creates value for the customers.

A Cyberphysical System Based Mass-Customization Approach with Integration of Industry 4.0 and Smart City

Smart city is a city which is designed to meet the people’s demands. In addition to use of sources efficiently, trends of people are also a need that smart city should meet. Buying personalized products in a cheap and fast way is a demand of people of today. Mass customization, which is defined as the personalization of products, achieves making the tailor-made products cheaper. In this study, we propose a new approach for mass customization with the integration of smart retail and smart production. With removing the operators and actualizing the progress autonomously, it is aimed to reduce the waiting time of customers. Because less waiting time means that there are more mass-customization customers, and this is expected to increase the popularity of mass customization. Thus, reducing wastes and increasing productivity are aimed. This study also constitutes the infrastructure that enables a production system to autonomously perform all stages from order to delivery. With the given scenarios, challenges and advantages of desired approach are discussed.

Maintaining customer-brand relationships in the mobile industry: the mediation effects of brand relationship benefits and quality

This study focuses on customers pursuing mobile products in order to attain brand relationship benefits (BRB). This research investigates the antecedents and consequences of BRB and brand relationship quality (BRQ) in the mobile industry. This research adopted structural equation modelling to test the proposed model and had a research sample of 310 smartphone consumers in Taiwan. The results indicate that fashion innovativeness and fashion involvement influence hedonic benefit from the fashion approach of customers' psychological attributes. From the utilitarian approach of product attributes on mobile, usability influences functional benefit, and convenience influences special treatment benefit. Hedonic benefit, functional benefit, and special treatment benefit, all influence BRQ. In addition, BRQ influences repurchase intention. BRB are the mediators between the antecedents and BRQ. BRQ is the mediator between BRB and repurchase intention. As an academic contribution, this study filled a void in this area, as most of the previous studies in this area focused on the influence of service relationship on the relationship benefits and relationship quality rather than on the influence of brand relationship issues. From a managerial standpoint, this study can assist mobile providers to understand which approaches influence customers' repurchase intention.

Three-Step Approach to QoS Maintenance in Cloud Computing Using a Third-Party Auditor

Cloud computing is a rapidly evolving service for potential clients who wish to outsource their data storage or subscribe to cloud services. In a data-driven society, every company needs to make cost-effective and responsible decisions in terms of how they handle their sensitive data. Should a company make the decision to use cloud services, they must complete the arduous task of not only choosing the right CSP for that particular firm, but also the constant monitoring of the data being stored and processed externally. In addition, under certain circumstances, there are laws that might prevent the firm from using certain CSPs. When using a cloud service, there is a need for ongoing agreements between cloud service users (CSUs) and cloud service providers (CSPs). Currently, this comes in the form of written agreements known as cloud service agreements (CSAs). CSAs contain information on the quality of service (QoS) that the CSP is promising to deliver to the CSU. However, CSAs can often be inflexible and unmaintained; therefore, there is a need for constant monitoring of the QoS being provided by the CSP. In this paper, we propose a model in which a third-party auditing body (e.g. cloud carriers, cloud brokers, cloud auditors) can assist a CSU in ensuring that they are receiving the promised services from their chosen CSP. To support this model, we propose a three-step approach for customers to evaluate the service-level agreement (SLA) of their CSAs. The three basic steps of our model are: an initial review of any valuable information useful to a CSA, an assessment of specific cloud metrics, and quarterly reevaluations of the CSA. Our proposed model will allow CSUs to be more confident that they are receiving the services they are subscribed to, as well as receiving the best QoS that a CSP can provide. With our model, any IT department, with the assistance of the third party, should be able to monitor and evaluate their cloud services and CSAs.

Perception of Local Food Labelling by Generation Z: Eye-Tracking Experiment

The subject of this research is to reveal the customer's approach towards local food in general and to explore the impact of its labelling on consumer perceptions. The main objective is to find out if an eco-label, a local-label or a bio-label has an impact on consumer behaviour. The following methods were used during the research: eye-tracking technology, in-depth interviews, the A/B testing method, the non-parametric Mann-Whitney test and the non-parametric Kruskal-Wallis test for testing hypotheses. Data were collected from the eye-tracking device in December 2015 and additionally revised for higher validation. In total, the observation contains 121 respondents (63 participants in the reference group - A, and 58 participants in the control group - B). Participants are defined as being from generation Z. It is assumed that the presence of the label on a product has an effect on consumer behaviour. The experiment itself took place at the eyetracking laboratory of the Faculty of Business and Economics at Mendel University in Brno.