Kinds Of Customers Research Articles

Optimization of a Two-Echelon Supply Chain Considering Consumer Low-Carbon Preference

This paper considers a fresh food supply chain with a supplier who takes responsibility for the cold chain and a retailer who needs to reprocess the fresh food. Carbon emissions will be produced in the processes of production, transportation, processing, etc. We consider the four-stage game, obtain the function expressions of optimal market prices with respect to carbon emission reduction level (CERL), analyze the best responses of the supplier and the retailer regarding their CERLs, and obtain the 25 optimal CERLs under competitive equilibrium. In 24 of the 25 equilibrium cases, the supplier or the retailer either do nothing to reduce carbon emissions, or make the most effort to reduce carbon emissions. Excluding these special cases, we focused on a non-trivial case where the increasing consumer preferences for low-carbon products will encourage the supplier and the retailer to reduce carbon emissions. Interestingly, we find that when the consumer preference for low-carbon products is low, the retailer’s and supplier’s equilibrium carbon reduction levels are low, so that the potential market size is small such that the competition for two kinds of customers is fierce. Then, an increase in the sale cost will reduce the retail price. However, when the consumer preference for low-carbon products is high, the potential market size is large such that the competition is not fierce. Then, an increase in the sale cost will advance the retail price.

Fintech and contactless payment: Help or hindrance? The role of invasion of privacy and information disclosure

PurposeThere is always a need to discover how a paradox between a customer’s desire for a more personalized experience and their privacy and security concerns would shape their intention to continue using contactless payment methods. However, personalization–privacy paradox has not been well-covered over the area of contactless payment. Therefore, this study aims to empirically examine the impact of personalization–privacy paradox on the customers’ continued intention (CIN) to use contactless payment.Design/methodology/approach – The empirical part of the current study was conducted in Saudi Arabia by collecting the primary data using online questionnaire from a convenience sample size of 297 actual users of contactless payment methods.FindingsBased on structural equation modeling, personalization and privacy invasion were approved to significantly impact perceived value of information disclosure (PVD). Strong causal associations were confirmed between perceived severity, structural assurance and response cost with privacy invasion. Finally, both PVD and privacy invasion significantly predict CIN.Research limitations/implicationsThere are other important factors (i.e. technology interactivity, technology readiness, social influence, trust, prior experience, etc.) were not tested in the current study. Therefore, future studies would pay more attention regarding the impact of these factors. The current study data were also collected using a convenience sample of actual users of contactless payment methods. Therefore, there is a concern regarding the generalizability of the current study results to other kind of customers who have not used contactless payment.Originality/valueThis study has integrated both personalization–privacy paradox and protection motivation theory in one model. The current study holds value in providing a new and complete picture of the inhibitors and enablers of customers’ CIN to use contactless payment, including new types of inhibitors. Furthermore, personalization–privacy paradox has not been fully examined over the related area of Fintech and contactless payment in general. Therefore, this study was able to extend the theoretical horizon personalization–privacy paradox to new area (i.e. contactless payment) and new cultural context (Saudi Arabia).

How Corporate Social Responsibility Boosts Corporate Financial and Non-financial Performance: The Moderating Role of Ethical Leadership.

Corporate social responsibility has always been considered an important topic, and many studies discuss the association between corporate social responsibility (CSR) and corporate performance, but the results are still inconclusive. This study is to examine the impact of CSR on corporate performance (financial and non-financial) with the moderating impact of ethical leadership. Data is gathered from 222 companies in Morocco using a simple random sampling technique. Moreover, for measuring customer satisfaction and corporate image in the kinds of customers targeted by the CSR activities of the firms, we collected data from customers and got 209 responses. For analyzing the results of this study, structural equation modeling has been used, while for moderation, the hierarchical regression technique has been adopted. Findings revealed a significant positive association found between CSR and corporate finance as well as non-financial performance (corporate image and customer satisfaction). Ethical leadership helps in increasing the financial and non-financial performance of an organization. The findings further revealed that ethical leadership moderates the relationship between CSR and firm financial and non-financial (corporate image and customer satisfaction) performance. This study will assist management in realizing the importance and implementation of CSR practices in organizations, especially in the Moroccan context.

Key Aggregation Cryptosystem and Double Encryption Method for Cloud-Based Intelligent Machine Learning Techniques-Based Health Monitoring Systems.

Cloud technology is a business strategy that aims to provide the necessary material to customers depending on their needs. Individuals and cloud businesses alike have embraced the cloud storage service, which has become the most widely used service. The industries outsource their data to cloud storage space to relieve themselves of the load of dealing with redundant data contents. This must be protected to prevent the theft of personal belongings, and privacy must be improved as well. Different research projects have been suggested to ensure the safe management of the information included within the data content. The security of current research projects, on the contrary, still needs improvement. As a result, this method has been suggested to address the security concerns associated with cloud computing. The primary goal of this study effort is to offer a safe environment for cloud users while also increasing the profit of cloud resource providers by managing and securely delivering data contents to the cloud users. The bulk of sectors, including business, finance, military, and healthcare industry, do not store data in cloud-based storage systems. This technique is used to attract these kinds of customers. Increasing public acceptance, medical researchers are drawn to cloud computing because it allows them to store their study material in a centralized location and distribute and access it in a more flexible manner. They were collected from numerous individuals who were being evaluated for medical care at the time. Scalable and enhanced key aggregate cryptosystem is a protected data protection method that provides highly effective security in the healthcare industry. When parties interested in a dispute disagree on the outflow of sensitive information, this technique manages the disputes and ensures the data security deployment of a cloud-based intelligent health monitoring system for the parties involved. The encrypted data structure of medical and healthcare prescriptions is recorded as they move through the hands of patients and healthcare facilities, according to the technique recommended. The double encryption approach is used in order to raise the overall degree of security. An encryption class is created by referring to the Ciphertext ID during the encryption procedure. The keyholder is a master secret key that facilitates in the recovery of the secret keys of various monsters and creatures by acting as a conduit between them. It is transferred and stored as a single aggregate for the benefit of the patient or customer in order to make decryption more convenient and efficient. A safe connection between cloud-based intelligent health monitoring systems and healthcare organizations and their patients may be established via the use of a key aggregation cryptosystem and a double encryption approach, according to the researchers. Because of this, when compared to earlier techniques, the findings reveal that the research methodology provides high levels of security in terms of confidentiality and integrity, in addition to excellent scalability.

Appointment window scheduling with wait-dependent abandonment for elective inpatient admission

ABSTRACT In this study, we propose a new appointment window scheduling (AWS) approach of informing customers of an admission window (AW) rather than the traditional appointment time. We provide a formal description of this AWS problem for only one kind of customer and propose a dedicated chance-constrained policy to assign AWs dynamically under the condition with fixed service capacity, different scales as well as status in different waiting stages, and wait-dependent abandonment. Numerical experiments show that customer satisfaction can be significantly improved (by reducing over 60% of wait-but-abandon events and by reducing 90% of departures caused by waiting beyond the AW), and server utilisation is slightly improved. And the improvements are more significant when systems are overloaded, and customers are more sensitive to online waiting than offline waiting. The AWS scenario can also be applied to other queueing systems as long as it is possible and profitable to let customers wait outside of the waiting area.

Negative eWOM Management: How Do Hotels Turn Challenges into Opportunities?

ABSTRACT In this digital age, the Internet provides angry consumers an easy means to vent their dissatisfaction. Negative communications shared among consumers exert a strong and destructive influence on hospitality business. The aim of this empirical study is to explore how upscale and luxury hotels in Hong Kong manage negative electronic word-of-mouth (eWOM) and turn the challenges into opportunities. Findings reveal that hotel managers perceived eWOM not only affects hotel reputation and business revenue, but also makes the management of customer expectation difficult. When developing a personalized management response to address customer feedback, hotel managers face the challenges of limited information about the incident and the complainer. Records of daily operations and documented incidents become good sources of internal information that facilitate effective investigation by hotel managers and fair judgments. Hotel managers also examine the demographic information, travel experiences, and records of the reviews the customers published on eWOM sites to ascertain the kind of customers involved and why these customers experience dissatisfaction. Positive eWOM motivates the management and the team to keep up their good work, whereas negative eWOM is customer-driven learning that drives hotels to identify the problems and make continuous improvement. Practical recommendations are made for eWOM management.

THE EFFECT OF DIGITAL PAYMENT SYSTEM ON FINANCIAL PERFORMANCE OF APDCL: A CASE STUDY

The main purpose of the study is to analyze the effect of digital payment in the financial performance of a State Owned Public Limited Company more precisely Assam Power Distribution Company Limited (APDCL). The research paper contains statistical analysis of the performance of Assam Power Distribution Company Limited after the implementation of digital payment system. The research paper is based on data available on the website of Assam Power Distribution Company Limited. Data has been collected from the audited final accounts uploaded by the company in their website. The paper will be beneficial to the company as well as to other public limited entities for future as it is mostly based on secondary data and analytical in nature. The very success of the new technology introduced by an organization depends upon the improvement in its financial performance. The effect of digital payment in APDCL case is quite positive and encouraging one. The customers of APDCL are using digital modes of payment effectively. The collection of revenue from all kind of customers is encouraged by the digital payment system. In near future also, digital payment system boosts the financial condition of the company. Five years future trend is predicted with the help of time series analysis which will benefit the company to compare the outcome with forecast. It will also help other public limited companies dealing with digital payment system and collection of revenue in such a way that it can relate the research with their entity and respond accordingly.

Assessing Direct Marketing Effectiveness at a Retailer’s: a Mixed-Effects Model of Heterogeneous Responsiveness to Personalized Promotions

This study proposed a mixed linear modeling framework for revealing the average treatment effects of coupon promotions as well as for figuring out what kind of customers are more responsive to coupon promotions. The analysis used detailed data on 2,469 households who are frequent shoppers at a retailer over one year. A series of models starting from fixed parameters OLS regression to more flexible random coefficient models were built. The results showed that receiving more coupon promotions does not lead to higher spending among households. None of the available demographic characteristics was significantly linearly related to the responsiveness to coupon promotions according the initial model with cross-level interaction terms. However, exploratory analysis of random slopes with the help of a regression tree allowed to correct the specification, which allowed confirming that people aged 25+ with annual household income exceeding $25,000 are more responsive, yet their response is insignificantly different from zero. Keywords: Mixed-Effects Model, Multilevel Analysis, Heterogeneous Responsiveness, Promotions.

Metode Alternatif dalam Pencarian Peringkat E-Commerce di Indonesia Berdasarkan Rating Pelanggan

The existence of the internet raises an online trading system using applications. The rise of online trading systems has triggered the emergence of various e-commerce in Indonesia that provide various kinds of customer needs. This also causes problems for customers, namely the difficulty in choosing quality e-commerce. The effort to overcome this problem is to rank e-commerce in Indonesia based on customer ratings. The method commonly used for ranking is the analytical hierarchy process (AHP) method, but in practice there are several variables that are not found in e-commerce so the AHP method cannot be used. The alternative method chosen is the ant colony optimization (ACO) method. The feasibility test of the ACO method in searching rankings for e-commerce data needs to be done because not all variables are in e-commerce. Simulations for ranking search are carried out using 2 generated data scenario with analytical hierarchy process (AHP) and ant colony optimization (ACO) method. The simulation results show that the ACO method is feasible to be used for ranking with blank data, then the application of the ACO method for e-commerce data in Indonesia. The best taboo results are based on the highest opportunity value and the highest correlation coefficient, namely in the second taboo, with three major ratings, namely JD, SP, and TP

Novel Deep Regression and Stump Tree-Based Ensemble Models for Real-Time Load Demand Planning and Management

The electrical power companies’ load consists of several kinds of customers, for example, agricultural, building, industrial, etc. Agricultural and industrial energy consumption is based on highly inductive loads, and it leads to the electricity shutdown because of highly inductive loads effect large spikes to the power curve. These spikes show their irregular disturbance in the electric power system due to shutdown and start-up of these large loads. It is considered irregular as well as a tough job to forecast the load with the existence of such kinds of spikes. Further, the heterogeneous and multi-source load consumption characteristics necessitate the integration of evolutionary models and the ensemble techniques render better robustness and forecast accuracy. For this purpose, we proposed the novel deep regression and stump tree-based ensembles models (DRTSEM) for accurate load planning and management with the use of highly inductive load data, buildings loads, etc. The hyperparameters e.g., network weight decay, network learning rate, the total number of hidden layers and momentum of the DRTSEM is optimized by using the deep regression and stump tree-based algorithms. For forecasting analysis, two different climate zones and seven model’s input model parameter selection (MPS) with new sets of the data samples are used. The forecasting performance is testified with the generalization network error and resubstituting loss, 10-fold cross-validated mean square error, four performance evaluation statistics and existing tree bagger (TB) model. The mean absolute percentage error is noted 47%, 64% and 41% better than the TB model at MPS-3 to MPS-5 respectively. The proposed DRTSEM can efficiently tackle the nonlinear characteristics of the heterogeneous and multi-source loads and moreover increase accuracy and reduce the error between actual and forecasted load demand. The modeling results proved that the use of DRTSEM renders more accurate utility energy planning and management compared with the existing ensemble approaches.

Kfc's promotional strategies and it's impact on brand equity

This study is based on the deep insights of marketing and promotional strategies adopted by KFC that have enhanced its brand equity in Indian market. The study stretches its understanding on how KFC's promotional methods impact the target audience to buy its products. Hence, promotional activities that leads to develop a brand image in the minds of target audience. It focuses on the key elements of promotional mix: namely Advertising, Sales Promotion, Personal Selling and Word of Mouth which KFC uses to communicate with present and potential customers. Though KFC's integrated marketing communication (IMC) involves several channels to convey the message, this study has indicated the most effective promotional component is Word of Mouth, through which the brand equity among customers is created at minimal cost. The main objective of this study is to examine the relationship between the promotional strategies and brand equity and find out to what extent the promotional strategy impacts on brand equity of KFC in Mysore district. Therefore, it explicates how KFC formulates promotional strategies with ongoing trends as it is essential to use the appropriate techniques that can help to stay connected with all kinds of customers in competitive markets.

Optimal Placement of Multiple Feeder Terminal Units Using Intelligent Algorithms

In order to solve the placement problem of three kinds of feeder terminal units (FTU) in the distribution network, this paper proposes a novel mathematical model. The model considers economic cost and electricity supply reliability from the perspective of life cycle cost. The reliability algorithm in this model is established for the distribution network configured with centralized feeder automation. Different evaluation indices of reliability and the importance of several kinds of customers are also considered in this model. Aiming at the reliability evaluation in this model, this paper puts forward the reliability analysis method for the distribution network with three kinds of FTUs. In view of the difficulty to express the reliability of distribution network in a formula with decision variables, and the non-deterministic polynomial hard (NP-hard) nature of this model, a variety of intelligent algorithms are applied to solve the model. The feasibility and effectiveness of the model and methods for FTUs placement optimization problem are verified by a case study of the Roy Billinton test system (RBTS) Bus 5 system.

Choices for competing service providers with heterogeneous customers: Traditional versus opaque sales modes

Competing service providers have been conducting opaque sales widely by cooperating with an intermediary, such as Priceline.com and Hotwire.com, to increase capacity flexibility, realise price discrimination and create a new channel for customers. Whether competing service providers should collaborate with an intermediary when facing heterogeneous customers and how a contract design can be made between service providers and the intermediary are two challenging research problems. Recent advances in opaque sales have focused on homogeneous customers, whereas the revenue sharing mechanism for heterogeneous customers has remained unexplored. This study considers two competing service providers that collaborate with an intermediary in a heterogeneous market with leisure and business customers. Styled models are built to capture the traditional and opaque sales modes. The contracting strategies are derived by comparing the profit of the two modes. Considering the simultaneous arrivals of two kinds of customers, we find that the decisions of service providers relate to two factors: the market structure and the revenue sharing mechanisms. In a high-pricing strategy market, service providers may collaborate with an intermediary. Conversely, in a low-pricing strategy market, service providers may not collaborate with an intermediary. In both situations, service providers should strive for a balance between the profit derived from the intermediary and the potential profit loss from opaque sales.

Experientially diverse customers and organizational adaptation in changing demand landscapes: A study of US cannabis markets, 2014–2016

Abstract Research Summary In this study, we contribute to strategy and organizational theories of organizational adaptation by developing theory about the kinds of customers that facilitate an organization's ability to adapt to changing demand‐side conditions. We propose that customers who have previously interacted with diverse types of organizations in the market convey informationally rich feedback that better enables organizations to understand and adapt to change—particularly in more rapidly changing contexts. We further expect that organizations that position themselves congruently with market preferences will be stronger market competitors. We test and find support for our arguments using a unique dataset of over 8,000 cannabis dispensaries operating in seven states that were listed on Weedmaps.com between July 2014 and June 2016. Managerial Summary Performance of organizations in changing markets depends on their ability to adapt to evolving customer preferences. Such adaptation requires understanding how preferences evolve—not only among existing customers, but also in the broader market in which the organization competes. We propose that feedback from customers who have previously interacted with diverse types of organizations in the market enables organizations to understand customer expectations and adapt to changing demand landscapes by positioning themselves accordingly. We find support for these arguments in legalized cannabis markets within seven U.S. states. Dispensaries that get more feedback from experientially diverse customers position themselves in ways that are more congruent with the preferences of customers in their market. Furthermore, dispensaries who are more congruent with market preferences survive longer, bring in a greater number of new consumers, and are generally more appealing to those consumers.

Simultaneous control on lead time elements and ordering cost for an inflationary inventory-production model with mixture of normal distributions LTD under finite capacity

The significance of inflation and time value of money in inventory/production systems is indisputable for modern decision makers. Consequently, the paper aims to study the influence of inflationary condition on a stochastic continuous review integrated vendor–buyer inventory system in the presence of a multilevel reorder strategy for the system. It is considered that lead time components and ordering cost are controllable. Lead time is decomposed into its components: set-up time, production time and transportation time. Based on lead time components, demand during the lead time for different batches is assumed to be a mixture of normal distributions. The objective is to minimize joint inventory expected cost by simultaneously optimizing ordering quantity, reorder points of different batches, ordering cost, setup time, transportation time, production time and a number of deliveries under space constraint while the lead time demand follows a normal distribution. To minimize the expected inventory cost, a Lagrange multiplier method is applied in order to solve the problem, and an iterative algorithm is designed to find optimal values. The behavior of the model is illustrated in numerical examples. It was found that for a fixed value of transportation time, setup time and number of batches, with an augment in inflation rate, the two optimal reorder points for different batches were increased. Also, optimum joint expected annual cost with inflation for two kinds of customers’ demand is larger than one kind of customers’ demand. Furthermore, sensitivity analysis and managerial insights are given to show the applicability of the model.

Two M/M/1 Queues with Incongruent Arrivals and Services with Random Feedback

SYNOPTIC ABSTRACTThe current study examines a queuing system with two incongruent arrivals and two services. In this regard, two types of customers enter the system by a Poisson process and the service times are assumed to have exponential distributions. After the first service is completed, the system may provide feedback to repeat the first service, leave the system, or continue to give the second service. The same policy is utilized for the other kind of customers. The whole stochastic processes involved in the system are considered as independent random variables. A probability generating function is derived for each type and for the system that yield the performance measures. We examine the validity of the results through numerical approaches.

Perceived Service Quality and Customer Satisfaction: A Missing Link in Indian Banking Sector

The purpose of the article is to recognize the moderating effect of customer knowledge on perceived service quality and customer satisfaction through customer value evaluation in the Indian banking sector. This knowledge can considerably streamline the effort banks invest in acquiring the right kind of customers. The results of the study indicated that perceptions of service quality positively impacted customer value evaluation. Moreover, customer knowledge strengthened the relationship that the empathy and responsiveness dimensions of service quality had with customer value evaluation and moderated the relationship that reliability and tangibility dimensions had with customer value evaluation.

Research on the slot allocation of container liner under E-commerce environment

The optimization of slot allocation of container liner is directly related to the benefits of liner company. Generally, there are two kinds of customers in the liner company, contract customers and scattered customers. With the development of e-commerce, more and more scattered customers choose online booking, the predictability and stability of booking slot get improved. This paper describes expected marginal revenue and reserved slots of scattered customers under the e-commerce environment and traditional environment respectively at first. Then, builds a model to maximize the revenue of liner company in the voyage, considering the transportation of empty container and next takes a fixed route of a liner company as an example to testify the model. Finally, according to the result, it comes to the conclusion that the e-commerce has good predicting effect and the total revenue of liner company under the e-commerce environment is greater than under the traditional environment. With the further development of e-commerce, the scattered customer under the e-commerce will replace the contract customer gradually.

Service Mechanism and Pricing Based on Fairness Preference of Customers in Queuing System

AbstractService providers often adopt the mechanism of customer classification due to the heterogeneity of customer waiting cost. However, the classification service may cause unfairness feeling of regular customers, then affect the revenue and social welfare. This paper provides the first exact analysis about the situation that service providers offer two classes of non-preemptive priority service when customer fairness perception is explicitly modeled. We model customer fairness perception as a negative utility on regular customers that’s proportional to the waiting time difference between the two queues. By analyzing a stylized M/M/1 queue in monopoly service system, we can derive important results some of which reaffirm existed research results. First, from the perspective of revenue maximization, service providers should also adopt the mechanism of customer classification and set up the two kinds of customers where they can see each other. Next, considering customer utility maximization, service providers should cancel the mechanism of customer classification, and keep one queue (regular customers) only. Then, from the perspective of social welfare maximization, service providers should also adopt the mechanism of customer classification but set up the two kinds of customers where they cannot feel each other. Finally, this paper concludes the optimal pricing based on customer classification in the above three different perspectives. This research shows important reference value and practical significance for service providers who adopt the mechanism of classification service.

Analysis of a two incongruent arrivals and services M/G/1 queue with random feedback

A queuing system with two incongruent arrivals and services is considered. Two kinds of customers enter the system by Poisson process and the service times are assumed to have general distribution. After first kind service completion, it may feedback to repeat the first service, leave the system or go to give second service. The same policy is applied for the other kind of customer. All stochastic processes involved in this system are independent. We derive the probability generating function for each kind and for the system that yield the performance measures. Some numerical approaches examined the validity of the results.