Different Categories Of Customers Research Articles

Development of a simulation model of the activities of a transport and forwarding enterprise in the organization of international road cargo transportation

The object of this study is the process of planning the work of a transport and forwarding company when serving different categories of customers who need organizational support for the delivery of goods by road transport in international traffic. The solved problem is due to the need to devise recommendations for organizing the work of forwarders when interacting with customers of transport and forwarding services that export or import different categories of cargo. A simulation model of the transport and forwarding company’s work in customer service was developed and implemented in the GPSS World simulation automation package. The model provides for the optimization of organizational and management processes in cooperation with customers of transport and forwarding services. When developing the model, the duration of the types of work in which freight forwarders are involved in the export and import of goods by road transport was taken into account. The model also predicts the probability of errors in the forwarder’s work and the duration of their elimination. The application of the developed model in practice will enable the owners of transport and forwarding companies to plan the full-time number of forwarders and the duration of service provision under different conditions of interaction with customers. The simulation results reflect the performance indicators of the enterprise in serving different categories of customers. This will make it possible to optimize the work of the enterprise by planning personnel support. At the same time, the duration of transport and forwarding services will be reduced by 10–15 %, the capacity of the enterprise will increase by 6–11 %, and the reliability of service provision will increase by 8–14 %

Joint pricing and inventory management in a competitive market using reinforcement learning: a combination of the agent-based and simulation-optimization approaches

ABSTRACT One of the most important tools is an appropriate pricing mechanism to attract more customers and increase profits. The retailers’ main question is how to set the prices and inventory policies to maximize profit in a competitive heterogeneous market in presence of non-zero lead time and lost sales. A reinforcement learning algorithm is proposed to create appropriate decision-making mechanisms for pricing. A coordinated inventory policy in a competitive environment reduces logistic costs and leads to a higher profit. We use a reinforcement learning algorithm to investigate the performance of a retailer in a competitive environment. An agent-based modeling experimental environment combined with a simulation-optimization method in which a virtual market has been reproduced is used. The market is not homogeneous with respect to customer behavior. It is assumed that the retailer uses (R, Q) policy where the lead time is a fixed amount (L), and the shortage is permissible. The quality, distance, service level, and price are factors that influence customers’ choices. The simulation results for some randomly generated examples show that the algorithm in the competitive environment can make more profit than other available methods and the combined utilization of simulation-optimization methods has been able to find better solutions for the hybrid model of pricing and inventory management considering customer behavior. The results of simulation for three different categories of customers (more sensitive to price, equally sensitive to price, quality and service level, and more sensitive to quality (indicate that the average profit for the proposed algorithm is higher than that of other examined algorithms.

Multitasking recurrent neural network for photovoltaic power generation prediction

With the increased uptake of renewable energy resources (RES), power generation from Photovoltaics (PV) cells is gaining momentum and heavily depends on environmental and meteorological conditions. Predicting PV power generation plays an important role in power management and dispatch optimization. Due to the scales of PV systems, the generation may vary significantly, which is difficult to have accurate PV power generation prediction over different categories of customers (e.g., residential, agricultural, industrial, and commercial) using a single model. In this paper, we define the PV power generation prediction as a multitasking prediction problem, where PV generation over each of the categories is modeled as a separate prediction task. To address this problem, we employ a recurrent neural network (RNN) as the predictor for each prediction task and propose a multitasking RNN (MT-RNN) framework. Instead of addressing each task individually, MT-RNN performs knowledge transfer among different tasks to improve the prediction accuracy of each task, where the knowledge is represented via connection weights and biases in each RNN. In comparison to several state-of-art deep neural network (DNN) models that solve each task individually, the superior performance of MT-RNN in terms of prediction accuracy is demonstrated.

Scope for feed-in tariff in a hydro-rich energy market−a case of Bhutan

To promote the use of renewable energy (RE), several types of RE policies have been implemented globally. Among these, feed-in tariff (FiT) is one of the most accepted mechanisms of pricing policy. However, choosing the best policy for a market with a high RE penetration is a challenge. A case of Bhutan is considered in this paper as the source of electrical energy is predominantly hydropower. Additionally, a generous subsidy is provided by the government to keep the electricity tariff to a minimum. Recently, there has been an increase in the advocacy and motivation for other forms of RE sources (RES) to supplement hydropower and increase energy security in Bhutan. Bhutan aims to achieve a total of 20 MW of non-hydro RES by 2025 as per the RE policy of Bhutan. However, Bhutan still does not have an RE pricing policy, and therefore, there is a need to institute a suitable pricing mechanism to accommodate the penetration of the planned non-hydro RES. This paper discusses the challenges in introducing FiT for non-hydro RES in an electricity market dominated by hydropower in Bhutan. Subsequently, recommendations are made in the wake of subsidised electricity tariff, which is the lowest in the region at 0.0171 USD/kWh for low voltage customers. FiTs for solar photovoltaic based on different categories of customers have been computed and proposed.

Financial regulation in the age of the platform economy

Platform businesses allow for collaboration with nontraditional partners and bring together different categories of customers, in the financial context savers and investors or lenders and borrowers, creating large, scalable networks of users. Their entry into finance promises potential benefits to consumers in the form of new products, lower prices, wider choice, and enhanced consumer experience. At the same time, their new business models and technologies potentially threaten the dominant position of traditional financial services providers and create challenges for regulators. Platform businesses can use their preferential access to customer data to skim off high-quality loans, leaving only low-quality customers for other lenders. Their ability to offer complementary nonfinancial services that cannot be supplied by FinTech start-ups and banks can make it difficult or unattractive for customers to switch to alternative providers. This danger is especially acute when BigTech firms have monopoly power in other markets that complement financial services.

A Novel Optimization Method for a Multi-Year Planning Scheme of an Active Distribution Network in a Large Planning Zone

Electric power distribution networks plays a significant role in providing continuous electrical energy to different categories of customers. In the context of the present advancements, future load expansion in the active distribution networks (ADNs) poses the key challenge of planning to be derived as a multi-stage optimization task, including the optimal expansion planning scheme optimization (EPSO). The planning scheme optimization is a multi-attribute decision-making issue with high complexity and solving difficulty, especially when it involves a large-scale planning zone. This paper proposes a novel approach of a multi-year planning scheme for the effective solution of the EPSO problem in large planning zones. The proposed approach comprises three key parts, where the first part covers two essential aspects, i.e., (i) suggesting a project condition set that considers the elements directly related to a group of specific conditions and requirements (collectively referred to as conditions) to ADN planning projects; and (ii) Developing a condition scoring system to evaluate planning projects. The second part of our proposed scheme is a quantization method of correlativity among projects based on two new concepts: contribution index (CI) and dependence index (DI). Finally, considering the multi-year rolling optimization, a detailed mathematical model of condition evaluation and spatiotemporal optimization sequencing of ADN planning projects is developed, where the evaluation and optimization are updated annually. The proposed model has been successfully validated on a practical distribution network located in Xiantao, China. The investigated case study and comparisons verify the various advantages, suitability, and effectiveness of the proposed planning scheme, consequently saving more than 10% of the investment compared with the existing implemented scheme.

The role of social platforms in establishing brand awareness for B2C e-commerce: empirical study

Social media are computer-mediated technologies that facilitate and create an online environment. Hence, firms can use such media as an effective marketing and advertising tool to reach different categories of customers locally and globally and create brand awareness. Little evidence is available of how social media tools influence the creation of brand awareness among consumers. Also, not all companies are successful in this endeavour. Therefore, more research is essential in this domain. In response, this paper offers a good opportunity to seek and study the key factors that might participate in establishing such behaviour and proposes a model for such phenomena. Results of the study showed that e-WOM, user-generated-content, and product quality have a positive significant impact on customer's establishment of brand awareness. The results contribute to understanding of the value-enhancing potential of social media campaigns and demonstrate how the perception of brands is influenced through this new communication channel.

The role of social platforms in establishing brand awareness for B2C e-commerce: empirical study

Social media are computer-mediated technologies that facilitate and create an online environment. Hence, firms can use such media as an effective marketing and advertising tool to reach different categories of customers locally and globally and create brand awareness. Little evidence is available of how social media tools influence the creation of brand awareness among consumers. Also, not all companies are successful in this endeavour. Therefore, more research is essential in this domain. In response, this paper offers a good opportunity to seek and study the key factors that might participate in establishing such behaviour and proposes a model for such phenomena. Results of the study showed that e-WOM, user-generated-content, and product quality have a positive significant impact on customer's establishment of brand awareness. The results contribute to understanding of the value-enhancing potential of social media campaigns and demonstrate how the perception of brands is influenced through this new communication channel.

QUALITY SEEKERS AS MODERATING EFFECTS BETWEEN SERVICE QUALITY AND CUSTOMER SATISFACTION IN AIRLINE INDUSTRY

The following research paper examines the impact that quality seeker have on the quality of services offered by an airline. Service quality has been determined to influence customer satisfaction. This study therefore looks into the role of quality seekers in influencing quality of services and customer satisfaction. The study was based on a scoping review of the existent literature. Scholarly articles provide convincing arguments for the relationship between quality of services and customer satisfaction. However, customer satisfaction varies from one customer to another. There is a gap in the research regarding different categories of customers and how they moderate the relationship between service quality and customer satisfaction. Quality seekers are a category of customers who are not influenced by prices. Rather, their focus is on the quality of services and products offered. They seek out information on all available options but choose the one which best meets their expectations in terms of quality. This paper analyses the influence of quality seekers on the level of quality of services offered, and the resultant effect on customer satisfaction.

ANALYSIS OF KEY INDICATORS THAT AFFECT THE EXPECTED BENEFIT OF CUSTOMERS WHEN USING LOYALTY CARDS

The aim of this paper is to define the significance of different indicators that affect the expected benefit of customers when using loyalty cards in the purchasing process in the retail sector. As the most important indicators that affect expectations while using loyalty cards, the following was tested: price discounts, more efficient service and rewards, personalized communication, payment option, better information, status symbols and additional benefits. The research was conducted on a sample of 552 holders of loyalty cards of the largest retail chains in selected Central Europe (CE) and South East Europe (SEE) countries. The values of indicators for different categories of customers and different markets can be determined based on the obtained results and conducted tests. The determined values of the indicators are the basis for the formation of a regression model that will serve the chain managers to optimize the loyalty programs in relation to the identified customer expectations.

О ценовой эластичности спроса на электроэнергию

The paper provides the econometric estimates of short-run and long-run price elasticities of electricity demand for different categories of customers. Both for residential and for non-residential sectors the estimates (in absolute value) of short-run price elasticity are low, while the estimates of long-run price elasticity are high. Consequently, long-run projections of electricity demand under expectations of increase of energy prices should take into account the long-run price elasticity. The estimates of short-run price elasticity for non-residential sector can be used in models of imperfect competition in the electricity market, under a number of assumptions, such as the absence or weak attention of the regulator, when possible strategies of economic agents (such as electricity suppliers in the spot market) may depend on the short-run price elasticity of demand.

The sales force sizing problem with multi-period workload assignments, and service time windows

This work introduces the sales force sizing problem with multi-period workload assignments, and service time windows. The motivation of the problem arises from a real life situation faced by a goods distribution company. The problem consists in determining the size of the sales force (i.e. the number of vendors to hire) and their daily schedules, within a planning horizon, to serve a set of customers in order to minimize the total nominal wage. There are different categories of customers and each customer has multiple time windows depending on the service day. Furthermore, the nominal wage of a hired vendor is determined by the most expensive category of the customers he serves. A mixed integer linear formulation and a heuristic are proposed for this problem. The performance of the heuristic algorithm is assessed over a set of instances adapted from literature. Computational results reveal the efficiency and scalability of the proposed procedure, providing a better tradeoff in terms of solution quality and running time than a commercial solver.

Characteristics of the Romanian energy market

This paper highlights the main characteristics of the energy market in Romania. Starting from the mode of organization and operation of the electricity market, there are revealed prices and tariffs for electricity for different categories of customers and their evolution in time. There are pointed also ways of setting electricity prices and tariffs, taking into account the expenditures actually recorded by economic operators.

The management level of logistics customer service industrial enterprise

This article deals with some aspects of the logistics service of industrial enterprise customers, current approaches to its management, namely, measurement, evaluation and optimization. It describes the effect of the level of customer service in the business results. How the concept of “logistics service users” is formulated. The author’s index of evaluating the effectiveness of the logistics customer service – “logistics leverage”. Author’s universal measurement system of the logistics maintenance level, serving industrial enterprise customers is presented, including 11 indicators criteria values and integral indicator. The optimal values of parameters can be different for different categories of customers who prefer low, medium and high level of logistics services. It substantiates the practical significance of the study through tested at Chelyabinsk Electrode Plant.

BPM for supporting customer relationship and profit decision

Purpose – As a response to increasing global market competition, companies in various industries tend to identify and manage customer relationship to increase profit performance. Companies commit more resources to identify their VIP customers and retain them by all means. The purpose of this paper is to develop a customer relationship management (CRM) business process management (BPM) model to identify airline customers with different degree of relationship and profit potential, and select the highly profitable customers for developing retention strategy and processes, and convert the less profitable into profitable corporate accounts. Design/methodology/approach – This study innovatively apply the well-known techniques including CRM and relationship marketing models, fuzzy analytic hierarchy process (FAHP), and technique for order preference by similarity to ideal solution (TOPSIS) in the BPM research. This novel approach analyzes longer term customer profit and value potential, and prioritizes corporate accounts as the basis for setting appropriate customer service levels and improving the CRM process. This hybrid model is able to capitalize on the benefits of these methods and offset their deficiencies. Most importantly, it can be customized to various industries without complex modification. Findings – This study uses data of an airline company to validate feasibility of the proposed CRM BPM model. The results indicate that this model is able to classify the customers based on various criteria and sub-criteria, thus allowing companies to introduce appropriate service levels to deal with different categories of customers, and improve CRM process so as to maximize customer profit and value potential. Practical implications – This CRM BPM model and analysis provide managers extensive customer knowledge, more analytical and fact-based decision-making support, and a stronger focus on return on investment in sales and marketing. Knowing the profit and value potential generated by individual corporate customer makes it easier to establish the link between the CRM and the profit outcome. This model also benefits the organization and its stakeholders by allocating more resources to the targeted customer relationships that are profitable or valuable, and makes marketing more accountable in its marketing programs. Originality/value – This study makes the first move to innovatively apply the well-known techniques including CRM and relationship marketing models, FAHP, and TOPSIS in the BPM research.

Customer-centric Compensation Plans: Linking Compensation Plans of Employees in Indian Restaurants with Expectations of Customers

The paper attempts at establishing alignment between compensation plans for employees in restaurants with customer preferences obtained by means of an exploratory research. The findings of the research indicate that food & beverage, cleanliness & comfort, assurance, personal attention, and special feeling are the dominant factors shaping customer expectations in India. Two different categories of customers were identified based on whether they prioritized dining experience or the tangibles associated with service. Ranking of priorities was done on the basis of the mean scores obtained in each of the factors mentioned above. For customers prioritizing tangibles, Special Feeling obtained the lowest score and featured at the bottom of the list. Food & Beverage, on the other hand, remained the top priority for customers across both categories. For the purpose of designing pay-for-performance plans, restaurants were categorized on the basis of their target customer segment. The percentage of variable pay was decided on two factors, (i) degree of control enjoyed by the employee and (ii) strategic importance of the particular function. The kitchen staffs were assumed to have suitable control over the Food & Beverage factor and the front-house staffs over the factors Assurance, Personal Attention and Special Feeling. To ascertain the strategic importance of a particular factor, the score obtained by it as well as its rank in the priority list were taken into consideration. Following this, suitable parameters for assessing the performance of employees were identified and their relevance discussed in some detail.

Who gains from hourly time‐of‐use retail prices on electricity? An analysis of consumption profiles for categories of Danish electricity customers

Studies of the aggregated hourly electricity load in geographical areas typically show a systematic variation over the day, the week, and seasons. With hourly metering of individual customers, data for individual consumption profiles have become available. Looking into these data we show that consumption profiles for specific categories of customers are equally systematic but quite distinct for different categories of customers. That is, different categories of customers contribute quite differently to the aggregated load profile. Coupling consumption profiles with hourly market prices which also include a systematic component in the hourly variation, we show that customers with different consumption profiles experience different average cost of their electricity consumption when billed according to hourly time‐of‐use prices. Thus, some categories of customers stand to gain from time‐of‐use pricing, while others stand to lose. In Denmark, typically industry, private services and households stand to lose, whereas agriculture and public services stand to gain from time‐of‐use pricing. However, differences within categories of customers are considerable and, for example, industrial companies running 24 h a day tend to gain from a time‐of‐use pricing. WIREs Energy Environ 2014, 3:582–593. doi: 10.1002/wene.120This article is categorized under: Energy Infrastructure > Economics and Policy Energy Policy and Planning > Economics and Policy

Long-term forecasting of hourly electricity load: Identification of consumption profiles and segmentation of customers

Data for aggregated hourly electricity demand shows systematic variations over the day, week, and seasons, and forecasting of aggregated hourly electricity load has been the subject of many studies. With hourly metering of individual customers, data for individual consumption profiles is available. Using this data and analysing the case of Denmark, we show that consumption profiles for categories of customers are equally systematic but very different for distinct categories, that is, distinct categories of customers contribute differently to the aggregated electricity load profile. Therefore, to model and forecast long-term changes in the aggregated electricity load profile, we identify profiles for different categories of customers and link these to projections of the aggregated annual consumption by categories of customers. Long-term projection of the aggregated load is important for future energy system planning, and the hourly load profile is an important input to energy system models that serves this purpose. In particular, these models often assume an unchanged hourly load profile (although the level may change). In contrast, our model suggests that the hourly load profile also changes as the shares of consumption by categories of customers change and new consumption technologies such as electrical vehicles and (for Denmark in particular) individual heat pumps are introduced.

Modelling and evaluation of microgrids reliability and operational performance and its impact on service quality

AbstractMicrogrids consist of a set of distributed generation (DG) facilities that operate for providing a reliable, cheap, efficient, and environmentally friendly supply to power customers. Additionally, their operation constitutes a significant feature in the framework of the competitive electric energy market being applied in many countries worldwide. This paper presents an efficient computational methodology that can be used for quantifying the reliability and operational performance of low voltage (LV) distribution systems with DG facilities that operate as microgrids. Special attention has been given to the simulation of the failures on the components of the microgrid feeders and the operation of normally open switches (NOS) that can be used for reducing their impact by connecting adjoining feeders. The developed methodology is based on the Monte‐Carlo sequential simulation approach that steps through time chronologically, by recognising that the status of a system component is not independent of its status in adjacent hours. The paper also includes the analysis being conducted for a typical LV distribution network that operates in a typical microgrid configuration with multiple feeders supplying different categories of customers (industrial, commercial, and residential) assuming alternative system planning schemes. These schemes include the operation of NOS through loop power flow controllers in order to provide the respective microgrid consumers with continuous and reliable supply when power outages occur, as well as the various technical and operational features of a large variety of microgrid DG facilities. Copyright © 2010 John Wiley & Sons, Ltd.

From Energy Sector Inquiry to Recent Antitrust Decisions in European Energy Markets: Competition Law as a Means to Implement Sector Regulation

This paper presents the conceptual path followed by European Union, European Commission and European Competition Network, after the Energy Sector Inquiry (2007) towards the realisation of the objective of an Energy Internal Market, fully functional and open to competition. Firstly, we examine the findings of Sector Inquiry and then we describe how the Third Energy Package - that followed - tried to address the issues highlighted by the Inquiry and how Third Energy Package introduces a promising but complex system, in order to develop sector rules. Following the above, we proceed to a brief but close examination of 10 recent -during or after Inquiry and the proceedings towards Third Energy Package - European antitrust decisions, which focused on several issues demonstrated by the Inquiry, such as: long-term energy supply contracts, market manipulation, vertical foreclosure, market partitioning, refusals to supply, discrimination between different categories of customers, strategic underinvestment, capacity hoarding and margin squeeze. All these cases except E.ON/GDF- were resolved under the commitments procedure of - Art. 9 of EU Regulation 1/2003 and the commitments mainly involved far-reaching structural remedies, such as ownership unbundling. Furthermore, we also investigate some recent mergers cases and some initiatives from selected European NRAs, in order to show the consistent character of competition policy in European Energy Markets.Following this analysis, we then proceed to Trinko case, in order to focus on two crucial and relevant to our analysis issues: essential facilities doctrine and the relation between sector regulation and competition law. After showing how Trinko case addressed these issues, we return to European Law and we examine the relevant point of view of European Competition Authorities. One major conclusion is that in EU, Commission applies competition law, in order to address issues fitting to sector regulation in a possibly stricter way than sector regulation does - for example Third Energy Package offers many alternatives to full ownership unbundling, while Commission's decisions actually present it as a single option; thus Commission tries to implement a sector specific policy by competition law means and methodology and especially by commitments procedure - a procedure that allows Commission to avoid ECJ investigation. We seek the reasons that lead to this approach and we highlight the weak points of it. Finally, we conclude that this approach may eventually lead to a dualistic system - possibly dangerous and inefficient as well - of addressing energy market's issues; a dualistic system that will fully reveal its possibly negative consequences after the Third Energy Package comes into force.