Target Revenue Research Articles

Financial Statement Forecasting and Financing

Using a “plug” figure or “slack term” within a pro forma analysis is the standard method to allow a forecasted balance sheet to have assets equal to liabilities and equity. Seemingly, different types of plug values are demonstrated to be mathematically linked to each other. Further, by exploring cash as a plug figure, a solution emerges for a “target revenue growth rate” in which cash is not depleted. If a private equity venture can generate revenue growth above the target revenue growth rate, cash will accumulate and improve the return on the private equity investment.

Multispecies Portfolios of U.S. Marine Fisheries: Ecosystem‐Based Fisheries Management Reduces Economic Risk

Fisheries management has focused on single stocks, not directly accounting for species interactions, and usually only considering economic factors in post hoc analysis. This approach has been successfully applied for many species over many years, but may also inadvertently result in greater risks being incurred. We demonstrate a portfolio optimization approach to inform a broader set of fishery concerns as a way to emphasize species interactions and economic considerations in resource management decision making. The approach can use readily available data on landings and revenue to generate easily digestible indicators of risk, namely the risk gap (i.e., the difference between actual and optimal portfolio values). Herein, we calculate portfolio efficiency frontiers that minimize risk for target revenue outcomes and resulting risk gaps for commercial fisheries using the top 25 landed‐value species in six U.S. fisheries regions. Most regions exhibited a risk gap on the order of US$20–50 million, collectively on average over $250 million. Risk gaps can be used as ecosystem‐level indicators to inform managers of the unnecessary risk being assumed for a given level of revenue for a portfolio of fisheries stocks, which can move us towards operational ecosystem‐based fisheries management.

Calculation of the target revenue water ratio of local waterworks considering economic feasibility

Calculation of the target revenue water ratio of local waterworks considering economic feasibility

The Analysis of Business Development Through Canvas Business Model Approach for Determining Post-pandemic Business Strategy: A Case Study in Smartplus Training and Consultant Management

In 2020, Indonesia experienced a period of deflation or a drop drastic in the development of the economy caused there is a Covid-19 pandemic. At the moment, the Indonesian government has various policies for community and actors' efforts to restore return Indonesian economy. The destination of the study is to help analyze development efforts in determining a strategy for the business post-pandemic through the canvas model business. The research object is the Smartplus Training and Management Consultant actors. The business model canvas method is used to develop business models to increase competitiveness. The results from this research showed that the need exists to change targets and add customer segments. So that could increase the value proposition, namely change target revenue streams with optimizing revenue in sales. It also adds to the customer segment obtained from online media, and with the existence change key resources will change key activities, and to support development efforts consultants need additional investment funds.

THE EFFECTIVENESS OF LAND AND BUILDING TAX REVENUE FROM CENTRAL TO REGIONAL TAXES AT THE PALEMBANG CITY REGIONAL REVENUE OFFICE

Law Number 28 of 2009 limits the object of regional taxes and levies collected by local governments, including the delegation of Land and Building Tax management to the Rural and Urban sectors. In this study, researchers want to know and analyze Land and Building Tax revenues from central to regional taxes at the Palembang City Regional Revenue Office. This study used comparative descriptive. The results of this study are as follows: first: the percentage of the target revenue of Land and Building Tax in the Rural and Urban sector of the Palembang City Regional Revenue Office in 2015 is 102.57% including very effective criteria. Second: obstacles that affect the level of effectiveness in Palembang City are differences in tax subject addresses, double printing occurs, human resource expertise is also still considered inadequate, the determination of tax objects that are not in accordance with the actual situation, taxpayer awareness and ability to pay taxes are not on time. Third: efforts to overcome obstacles that affect the level of effectiveness of Land and Building Tax revenues, namely updating data or updating Land and Building Tax, distributing forms evenly to taxpayers, training human resources (employees of the Regional Revenue Office), coordination with the Land Agency for Land Zone Value.

Proposed Business Strategy for Company X

In 2019, Covid outbreak affect business situation that leads to decline due to lockdown and economic fall. However, Covid-19 pandemic create opportunity for IT sector to grow. Reflect the situation, in 2020 to 2021, company X suffered loss in income as of minus 903,167,461 rupiahs. The company suffer 5.33% and 9.16% revenue decrease in 2021 and 2022, and target revenue was not achieved. This research is conducted to assess internal and external factors that affect company X profitability and formulate strategy based on the problem occurred. This research is using qualitative approach with data collected through literature review, observation, and in-depth interviews with company X.

Sustainable Management and Environmental Protection for Basin Water Allocation: Differential Game-based Multiobjective Programming

It is important to manage water resources via emergy theory and its implementation mechanism for water dispatching while considering both economic development and environmental needs. The contribution of this paper is to propose a multi-objective dynamic differential game that can determine the optimal tax rate (OTR), optimal trading quantity of water (OTQW) in each province, and optimal bargain price (OBP) to balance resource consumption, economic development and environmental protection. Considering the sustainability of the ecological environment, the quantification of negative sewage value and net carbon emission constraints are introduced into the water allocation. To maximize the target revenue functions, minimize the net carbon emission constraints and obtain sustainable equilibrium solutions in this triple-level game, the costate function, Hamiltonian, and Lagrangian multiplier method are introduced. Then, a water dispatching structure is constructed for error correction between the predicted and actual runoff of the YRB. Taking the Yellow River Basin as an example, the validity of the proposed framework and solution method were verified under different hydrological years, with 6.5% ~ 9.1% higher economic benefits than other schemes and 4.3% ~ 5.9% lower net carbon emissions than other schemes. Compared to previous studies, this scheme can better meet the requirements of sustainable development and environmental protection.

Enhance Document Contextual Using Attention-LSTM to Eliminate Sparse Data Matrix for E-Commerce Recommender System

E-commerce has been the most important service in the last two decades. E-commerce services influence the growth of the economic impact worldwide. A recommender system is an essential mechanism for calculating product information for e-commerce users. The successfulness of recommender system adoption influences the target revenue of an e-commerce company. Collaborative filtering (CF) is the most popular algorithm for creating a recommender system. CF applied a matrix factorization mechanism to calculate the relationship between user and product using rating variable as intersection value between user and product. However, the number of ratings is very sparse, where the number of ratings is less than 4%. Product Document is the product side information representation. The document aims to advance the effectiveness of matrix factorization performance. This research considers to the enhancement of document context using LSTM with an attention mechanism to capture a contextual understanding of product review and incorporate matrix factorization based on probabilistic matrix factorization (PMF) to produce rating prediction. This study employs a real dataset using MovieLens dataset ML.1M and Amazon information video (AIV) to observe our ATT-PMF model. Movielens dataset represents of number sparse rating that only contains below 4% (ML.1M). Our experiment report shows that ATT-PMF outperforms more than 2% on average than previous work. Moreover, our model is also suitable to implement on huge datasets. For further research, enhancement of product document context will be a good factor in eliminating sparse data problems in big data problems.

Decision dilemma at Biziga

Learning outcomes The learning outcomes are as follows: introduce the concept of the decision-making process, decision-making unit and hierarchy of effects and marketing strategy; identify the critical aspect of segmentation, targeting and positioning; and highlight the critical element of pricing and communication media. Case overview/synopsis In early January 2017, Mr Ashish and Mr Rahul, co-founders of Biziga, a company engaged in training through simulation for management education, was at crossroads. Keeping in view the challenges of the emerging Indian market, Biziga envisioned creating participant-centric business learning simulations. The initial responses and feedback received from several top B-schools were promising. However, the euphoria did not last long. Biziga retained only a few of its initial clients from the Tier-1 B-schools who had adopted the product. But the response received from other categories of B-schools was not very encouraging. Acquiring new clients from these institutes was the major challenge. The founders of Biziga had differences in their thought about the strategic path they should pursue to achieve future growth. There were several options to achieve the goal of a target revenue of INR 1bn in the next five years and be known as a virtual gamification company with a complete bundle of business simulation products. They had to finalize for the financial year 2017-18 the most feasible and promising option/s that would have a long-term impact on the company’s future growth and success in the upcoming meeting scheduled in the last week of February 2017. Complexity academic level Postgraduate students and executive students. Supplementary materials Teaching notes are available for educators only. Subject code CSS 8: Marketing.

Adaptive Optimal Management of EV Battery Distributed Energy for Concurrent Services to Transportation and Power Grid in a Fleet System Under Dynamic Service Pricing

Deployment of electric vehicles (EVs) in a fleet system to deal with environmental issues has been at the center of attention over the past several years. While the battery of each EV offers small storage, hundreds of EVs collectively can offer large energy storage to serve a power grid. This article develops a model for a central controller in a fleet system that allows adaptive utilization of EV batteries distributed energy for concurrent services to the transportation and power grid. The optimization model integrates various slack variables and control parameters for managing real-time fare prices, adaptive energy, and reserve margin allocation, interaction with the grid operator, and meeting the fleet target revenue. The proposed model incorporates EV driver's input into the scheduling process to allow the driver to flexibly manage their battery capacities based on their availability and assessment of the transportation services demand. A dynamic pricing mechanism is developed for real-time calculation of fare rates to allow the EV fleet optimization problem to achieve a daily revenue target while limiting fare prices in a competitive market. Numerical results indicate that the model can manage several EVs for various services while enhancing the fleet financial metrics.

Learning From Highly Effective Teams: What Can We Apply to the Gastrointestinal Endoscopy Unit Team?

Learning From Highly Effective Teams: What Can We Apply to the Gastrointestinal Endoscopy Unit Team?

The Application of Revenue Management in Chilled Storage Area Allocation: Simulation Study

Resource planning in service industries is a difficult task and quite different from resource planning in manufacturing. Revenue management is one concept used in service industries when capacity and inventory are challenging to identify. In this study, the company case study provides chilled storage areas for customers. Different products are served and service charging is calculated based on the product’s weight and storing time. Currently, the target revenue cannot be achieved. This study presents the application of revenue management in chilled storage area allocation. From a previous study, there were four classes of products based on their importance level as A, B, C and D. Among all classes, the cost of under and overestimating demand was calculated for setting up the area allocation by following the concept of revenue management. Monte Carlo simulation was applied to simulate the existing and improved systems. The simulation results indicated that the average daily revenue could be improved when the storage area allocated to the lowest priority class (class D) was limited to be equal to the average daily demand of class D. Applying the proposed policy can help in increasing yearly revenue by approximately 73,638.75 Thai Baht. Finally, the implementation of the proposed procedure was discussed under the concept of Logistics 4.0.

Dynamic ticket pricing of airlines using variant batch size interpretable multi-variable long short-term memory

Research of airlines shows that seat inventory control and therefore, revenue management is based not on a systematic analysis but more on human judgement. Machine learning models have been developed and applied to support decisions for ticket pricing dynamically. However, conventional models and approaches yield low statistical evaluation scores. In this study, the features used in other studies were explored and the cost available seat kilometer (CASK) value and target revenue features were included for the first time to the best of our knowledge which are essential components of ticket price decision. Real data from a low-cost carrier airline in Turkey were collected and the observation data were splitted into two to study with the highest profit sale data. Then the outliers were filtered to let the models learn from and generate better price offerings businesswise. Observation datasets obtained in each step were recorded to be tested. 7 different model techniques were simulated and tested with 4 different datasets according to 6 different statistical evaluation criteria. A new approach to Interpretable Multi-Variable Long Short-Term Memory (IMV-LSTM) model was proposed by taking every flight and its sales as an independent series, that is to assign a dynamic batch size. Extensive experiments on real datasets reveal enhanced statistical evaluation scores by using the proposed approach and model. The proposed model can be used by the airlines to mitigate human judgement on ticket pricing, to manage their price offerings to reach their target revenues and to increase their profits. The model can be used by other business cases that have similar historical data as overlapping windows structure.

Assessment of Forest Personnel Performance in Akwa Ibom State, Nigeria

This study assesses the performances of forest personnel in Akwa Ibom State in meeting their target revenue for the state using qualitative and quantitative approaches. The primary data were obtained using a structured questionnaire, oral interviews, and direct observation, while the secondary data were obtained from all the 31 Divisions and the Directorate of Forestry in Akwa Ibom State. Data collected were analyzed using the descriptive and stochastic frontier analysis to assess efficiency The results obtained showed that the majority of the respondents were male (59.50%), in their economically active and productive age bracket (50.41), attended tertiary education (79.33%), were married (69.42%), had a family size of fewer than 5 members (71.90%), and received a monthly income of ₦41,000 - ₦50,000 (42.15%). Also, the majority of the respondents had been in service for 11 – 15 years (30.23%), resided in their stations (72.09%), and received various forms of in-training (65.12%) to enhance their effectiveness or performance. Most of the Uniformed Field staff patrolled their divisions daily with their superior visiting their divisions more than once a month. The majority (53.84%) of the Forest Officers had less than 10 years' experience and their technical efficiency ranged from 0.35 to 0.97. The study, therefore, recommends that a more conducive working environment should be provided for the forest personnel to be able to optimize their performances which would translate to increased revenue generation for the state.

ОСОБЛИВОСТІ ТА ПРІОРИТЕТИ ІННОВАЦІЙНОГО РОЗВИТКУ ПІДПРИЄМНИЦЬКИХ СТРУКТУР В СУЧАСНИХ МІНЛИВИХ УМОВАХ

The article discusses the features of innovative development of business structures in modern changing environment. After all, the transformational effects of the introduction of information and telecommunications technologies, which extend to all areas of socio-economic activity, necessitate a radical revision of the principles of management of innovative development of the national economy. Entrepreneurs who focus on the latest products and services, continuous and stable implementation of technologies, product renewal policies, organization of production in order to strengthen their competitiveness in the market in the selected segment, must set appropriate priorities for innovation and development. According to the results of the analysis of the main indicators of innovative development of domestic business structures, it is determined that the implementation and development of innovations in the enterprise is directly proportional to the invested funds, stable target revenues and well-formed strategy. The article considers and analyzes the main state tools to support and stimulate innovation of domestic business structures. Based on the results of the study of the peculiarities of the functioning of the national innovation system and mechanisms of knowledge transfer, the article presents the scheme of innovation partnership, which would ensure the effective functioning of the national innovation system. In addition, the article proposes a structural and logical model of the management system of innovative development of business structures, which provides support for continuous targeted innovation, has a cyclical form of operation and takes into account at all stages mechanisms of control, adjustment, adjustment of innovation processes using both internal and external innovation resources. The prospects of innovative development of domestic business structures are outlined in this work too.

EFFECTIVENESS OF TAXPAYER EDUCATION ON TAX COMPLIANCE FOR SMALL AND MEDIUM ENTERPRISES IN KENYA: A STUDY OF SELECTED BUSINESS ENTERPRISES IN KITENGELA TOWN IN KAJIADO COUNTY

This research paper aim was to establish the effectiveness of taxpayer education on tax compliance for SMEs in Kitengela town. There are reasons why KRA never met its revenue targets and the revenue collected has never surpassed the target set aside by the commission. The non-compliance of tax by SMEs can be attributed to the tax gap that is available in every fiscal year. KRA conducts taxpayer education to all registered SMEs in an effort to improve the existing level of tax compliance. The only way KRA will meet their target revenue is when they include all SMEs in the generation of the revenue. The study was anchored on Theory of Reasoned Action and Fisher Tax Compliance Model while the study variables were PAYE form of tax, tax rates, tax compliance cost, tax penalties and fines. The target population of the study were 1400 SMEs with a sample that was random stratified chosen of 140 SMEs. The data was analyzed using descriptive statistics, inferential statistics and SSPS version 24.0. The inferential statistics was employed to establish the relations that exist between the study variables. Pearson correlation matrix was used for predicting and describing the variables in terms of directions and magnitude while regression analysis was conducted at a level of 5%. The data analysis tools will be SSPS and the use of inferential statistics. The study established that the effectiveness of taxpayer education on tax compliance and all the predictors as shown by beta coefficients: PAYE (? = 0.542); tax rates (? = 0.482) and tax penalties and fines (? = 0.632). However, the study established there is a positive but statistically insignificant relationship (? =0.06, p= 0.671>0.05) between tax compliance cost and tax payer education. The study concluded that tax rates, PAYE, tax penalties and fines contribute greatly to tax compliance and finally tax compliance cost have the most significant influence on tax compliance. The study recommends that KRA should have an office in every county that will address tax issues at county level and the services to be offered should include tax penalties, filing of tax returns, tax computation and tax differentiation.

Improving decision-making in maintenance policies and contract specifications for infrastructure projects

In large infrastructure projects, the government frequently delegates the execution and management to a private through Public–Private Partnerships (PPP) type contract. However, both parties often have conflicting interests; i.e. while the private wants to maximise the profit, the government aims at maintaining a high-performance level. This paper presents a model to define a set of contract parameters that maximise the utility of both entities in the long term, and at the same time optimise the system performance. Moreover, it proposes a strategy for the private to decide the optimal maintenance frequencies and achieve its target revenue. It also describes the complex interactions between the public, the private and nature (i.e. all environmental aspects that influence the system’s performance). The model combines the advantages game theory, simulation, optimisation and agent-based modeling. A set of 72 types of Build-Operate-Transfer (BOT) contracts are simulated, with a sensitivity analysis on the main contract variables (i.e. minimum level of performance required, mean frequency of government inspections, and penalty fee in case of noncompliance). The results show the importance of flexibility in decisions when facing different sources of uncertainty, and in reducing information asymmetry between the parties to improve maintenance decisions.

Matching Users' Preference under Target Revenue Constraints in Data Recommendation Systems.

This paper focuses on the problem of finding a particular data recommendation strategy based on the user preference and a system expected revenue. To this end, we formulate this problem as an optimization by designing the recommendation mechanism as close to the user behavior as possible with a certain revenue constraint. In fact, the optimal recommendation distribution is the one that is the closest to the utility distribution in the sense of relative entropy and satisfies expected revenue. We show that the optimal recommendation distribution follows the same form as the message importance measure (MIM) if the target revenue is reasonable, i.e., neither too small nor too large. Therefore, the optimal recommendation distribution can be regarded as the normalized MIM, where the parameter, called importance coefficient, presents the concern of the system and switches the attention of the system over data sets with different occurring probability. By adjusting the importance coefficient, our MIM based framework of data recommendation can then be applied to systems with various system requirements and data distributions. Therefore, the obtained results illustrate the physical meaning of MIM from the data recommendation perspective and validate the rationality of MIM in one aspect.

Buzzfeed Inc: native advertising the way forward?

Learning outcomes This paper aims to understand the changing landscape of media and entertainment industry, to understand the difference between display advertising and native advertising, to know the standing of BuzzFeed in the industry and to know the strategic actions of BuzzFeed under the current competitive business environment. Case overview/synopsis Founded in 2006 as a viral lab, by Jonah Peretti and John S. Johnson, with the aim of tracking viral content, it caused disruption in the market with its entry and grew very rapidly. It was valued at $1.5bn in 2015, having raised money from numerous investors. The revenue of BuzzFeed was driven by the concept of native advertising. Catchy headlined articles conveyed the sense that BuzzFeed might be charging advertisers on basis of clicks, but this was not entirely true. Instead, BuzzFeed charged a fee from its clients for creating custom content targeting the customer base of the client. However, the year 2015 went tough for BuzzFeed when, as per the reports by Financial Times, it fell short of achieving its targeted revenue of US$250m by US$80m. It forced the company to revise and lower its target revenues for the year 2016 as well. The combined worldwide traffic to BuzzFeed saw a decline of up to 14 per cent. As Claire marketing head looked out of the window and pondered over the slashed revenue projections and the content related issues, the question on her mind was would native advertising sustain BuzzFeed in the longer run? BuzzFeed was known for its viral content and native advertising would involve finding a balance between what is good for the advertisers' brand and what will become viral. Buzzfeed ran a risk of losing brands to other modes of advertisement if they felt that native advertisement, which disguises the product within the content, was not meeting their expectations. Complexity academic level The case is targeted at students of post-graduation and under-graduation programs in Business Administration. Supplementary materials Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes. Subject code Marketing

The Effect of Money Ethics Toward Tax Evasion with Gender and Materilalistic as A Moderating Variable

Tax is one of the important elements in the revenue budget in Indonesia. Revenue from this sector is always strived to meet the target revenue. In some times the amount of tax receipt is always not in accordance with the targets set. Tax evasion efforts made by the taxpayer is important to get the attention of the state. This study aims to conduct testing and analysis of tax evasion efforts made by the taxpayer. Tests and analysis is done by using variable approach of money ethics, gender and materiality to tax evasion.Populasi in this research is taxpayer SME registered in Tax Office Primary Kudus. Sampling technique used with convinience sampling method. The number of samples used in the study were 118 respondent. Data collection is done by dividing the questionnaire on the respondent. While the data analysis technique used is the regression analysis by using the absolute differences. The results of this study are as follows: 1), money ethics has significant effect on tax evasion; 2), gender variables as moderators proved to strengthen the positive relation of money ethics to tax evasion; 3) while the materiality variable does not moderate the significant positional relationship of money ethics to tax evasion