Price Flexibility Research Articles

Microsoft's Strategic Advantage: An In-depth Analysis Based on Porter's Five Forces Model

Abstract: This article uses Michael Porter's five forces model to analyze Microsoft's competitive situation in the global technology industry. It emphasizes that Microsoft has maintained its industry leadership by continuously innovating its technology and being keenly aware of market changes. The analysis covers Microsoft's strategies in facing market competition, the threat of new entrants, the challenge of substitute products, the bargaining power of suppliers and buyers, and its impact on the company's performance. The study pointed out that Microsoft has established high barriers to entry in its main business areas, thereby effectively preventing the entry of new competitors. The article also analyzes how Microsoft maintains its competitive advantage and market leadership through product differentiation, innovation, flexible pricing strategies, and the ability to adapt to market structure. Although Microsoft faces many challenges, it has successfully maintained its competitiveness in the global market through solid R&D capabilities, an extensive product portfolio, deep market penetration, and an active response to changes globally.

Innovative Management Strategies and Competitive Advantage of Global System for Mobile Communication (GSM) Service Providers in Taraba State, Nigeria

This study investigates the effects of product, service, process, and technological innovations on the competitive advantage of GSM service providers in Jalingo, Taraba State, Nigeria. It aims to determine how these different types of innovations influence market positioning and operational efficiency within the regional telecommunications sector. The research is framed using Dynamic Capabilities Theory, which emphasizes the role of strategic adaptability and resource reconfiguration in achieving and sustaining competitive advantage in rapidly changing markets. Employing a mixed-methods approach, the study integrates quantitative data from structured questionnaires distributed to 115 staff across major telecom providers and qualitative insights from industry reports. A total of 102 responses were analyzed using regression analysis in SPSS to evaluate the effect of innovation types on competitive advantage. The findings reveal that all types of innovation—product, service, process, and technological—significantly enhance the competitive advantage of GSM providers in Jalingo. Service innovation showed the strongest effect, followed by technological, product, and process innovations. The study underscores the critical importance of a holistic innovation strategy that includes diverse forms of innovation to improve competitive advantage. GSM providers in Jalingo who embrace comprehensive innovation strategies are more likely to secure greater market share and achieve long-term profitability. The study recommends that GSM service providers should prioritize developing new service offerings and enhancing existing services. This could include investing in customer relationship management systems to personalize services, implementing loyalty programs, or introducing flexible pricing models that cater to different customer segments.

A two-layer strategy for sustainable energy management of microgrid clusters with embedded energy storage system and demand-side flexibility provision

The intermittent nature of renewable energy generation and the fluctuating demands pose persistent challenges in microgrid operations. In response, stakeholders and operators have turned to clustering the geographically adjacent microgrids as a solution. In this context, this paper introduces a novel two-layer energy management strategy for microgrid clusters, utilizing demand-side flexibility and the capabilities of shared battery energy storage (SBES) to minimize operational costs and emissions, while ensuring a spinning reserve within individual microgrids to prevent load-shedding. In the lower layer, the proposed approach devises optimal day-ahead operation policies, while the upper layer employs a cooperative strategy to further optimize the operational efficiency across the entire cluster. The energy management problem is accurately formulated as a mixed integer quadratic programming (MIQP) optimization, which incorporates linear terms in the problem's constraints. The formulation accounts for operational costs associated with SBES including expenses of charging/discharging and changes in operating states (CiOS). Real-world case studies with a cluster of three microgrids in Australia validate the effectiveness of this approach. Results show a reduction in operational costs for the base case scenario by 6.96 % compared to conventional microgrid management strategies. Sensitivity analyses further demonstrate the economic benefits of varying SBES capacity and flexibility pricing, with savings ranging from 6.5 % to 8.1 %. The proposed strategy also reduces CO2 emissions by up to 11.6 %, while improving system reliability. This strategy holds promise for integration into distributed energy systems with high renewable penetration and clustered local grids, offering significant advantages for utility operators and end-users through improved energy efficiency and reduced emissions.

Energy shocks as Keynesian supply shocks: Implications for fiscal policy

This paper analyses the economic impact of and the optimal policy response to energy supply shocks in a flexible price model with heterogeneous households. We introduce energy as a consumption good on the demand side and as an input to production on the supply side. A distinguishing feature is that, in line with empirical evidence, we allow households’ energy demand to be non-homothetic. The model provides three main insights. First, (negative) energy supply shocks act as a (negative) demand shock, or Keynesian supply shock, when two conditions are met: On the demand side household income inequality needs to be large, while on the supply side, the price elasticity of consumption goods needs to be high. Second, the social planner can implement the first-best allocation by subsidising firms and poor households while taxing rich households. Energy shocks then act as standard supply shocks. Last, issuing public debt can help implement the first best allocation when energy shocks are large and/or the economy’s overall energy intensity is low.

Optimal fiscal policy in small open economies with habit persistence

Abstract This paper sets up a small open economy model with habit persistence in consumption in which distortionary taxation is available in a flexible price environment. In open economy, the habit persistence in consumption aggravates the terms of trade externality, absent in closed economy, calling for more aggressive fiscal policy. While optimal labor income taxes are time-invariant in a closed economy with internal habit, they should be time-varying in an open economy to alleviate the terms of trade externality, even if the intertemporal elasticity of substitution equals the intratemporal elasticity of substitution. In a small open economy composed of households with habit persistence in consumption, households’ decision to gradually adjust their consumption and labor hours intensifies the undesirable terms of trade externality or the terms of trade channel. This generates a time-varying wedge between the efficiency conditions of the Ramsey planner and the market equilibrium conditions, calling for a time-varying taxation which takes into account the intertemporal elasticity of substitution and the intratemporal elasticity of substitution between home and foreign goods, in addition to the degree of habit and goods market distortion. The volatility of optimal tax rate increases with the degree of habit, whether households have external or internal habit. The volatility of tax rate shows an inverted U-shape in the degree of openness in the small open economy with habit. Finally, the optimal labor income tax rate moves countercyclically for low degree of intratemporal elasticity of substitution, while it moves procyclically for high degree of intratemporal elasticity of substitution.

Inflation targeting and output stabilization in an estimated monetary model

This paper studies determinacy conditions in a monetary model with an interest rate rule. In addition to the inflation rate as an argument of the policy rule, we introduce a second argument: output, a case empirically relevant but overlooked in the existing literature on monetary models with flexible prices. Firstly, we estimate a model with money in utility and the production function. We find that an aggressive response to inflation does not necessarily guarantee determinacy anymore. Secondly, we compare monetary policy in the pre-Volcker era and the post-Volcker era. We find that, after the appointment of Paul Volcker, the Federal Reserve started to respond more aggressively to inflation and less aggressively to output. Indeterminacy is pervasive: the equilibrium is indeterminate in both sub-samples. Thirdly, we estimate the impulse response functions. We find that monetary shocks, sunspot inflation shocks, and productivity shocks have long-lasting effects on inflation, output, and interest rates.

Perbandingan Metode Machine Learning dalam Analisis Sentimen Komentar Pengguna Aplikasi InDriver pada Dataset Tidak Seimbang

The InDriver service is an online transportation service that has more flexibility in price and driver choice by consumers. Various comments from InDriver service users can affect people's views, so it is necessary to carry out a sentiment analysis of these comments. The purpose of this study was to identify positive, negative and neutral sentiments in user comments and to compare the performance of classification methods. The results of analysis with unbalanced datasets show that the Support Vector Machine (SVM) and Logistic Regression methods have the highest accuracy, reaching 89%. However, quality assessment is not only based on accuracy alone. In terms of the balance between precision and recall in the minority (neutral) class, the Random Forest method shows a more balanced performance with an F1-score of 55%. After balancing the dataset with the SMOTE method, performance increases significantly for the Naïve Bayes Classifier method, especially in the neutral class for recall and F1-score metrics of 57% and 52%. In conclusion, SVM and Logistic Regression have high accuracy, but to consider the balance of precision and recall in the minority class, the Random Forest method is recommended.

Strategic Optimization of Conveyor Belt Splicing Solutions: Enhancing Competitive Edge in the Asia-Pacific Market (Case Study: Inspirare Luxiner Group)

The Asia-Pacific region, marked by rapid industrial growth and significant mining activities, offers both opportunities and challenges for companies in the conveyor belt splicing materials market. IL Group, known for its high-quality RARE System, has seen a decline in sales within this competitive environment. The centralization of manufacturing in Atlanta has led to long lead times and high logistics costs, reducing the company’s competitiveness. Moreover, insufficient after-sales support and integration challenges with client systems have further decreased customer satisfaction and retention. This research aims to identify the primary factors behind the RARE System’s decreased sales and to develop strategies for optimizing it to attract and retain clients. Additionally, it seeks to recommend business strategies to enhance IL Group’s competitiveness in the Asia-Pacific market. Data collection involved interviews and surveys with clients and internal stakeholders. The data was analyzed using thematic analysis, root cause analysis, SWOT & TOWS analysis, and Porter’s Five Forces framework. The study found that logistical challenges from centralized manufacturing, inadequate support, intense competition, and integration issues with client systems were key factors driving sales declines. To address these issues, the research recommends that IL Group establish regional manufacturing facilities to reduce costs and lead times. Improving customer support through regional centers and robust CRM systems is also essential. Investing in continuous R&D for product innovation will keep the product relevant and appealing. Implementing flexible pricing models and targeted marketing, along with forming strategic local partnerships, will further enhance competitiveness. By proposing these strategies, this research contributes to strategic business management. It offers practical solutions to enhance operational efficiency and market competitiveness. These strategies provide a structured approach to overcoming key challenges and achieving sustainable growth in the Asia-Pacific market.

Environmental Analysis and Management Suggestions of Starbucks Based on SWOT Model

We analyzed the advantages and disadvantages of Starbucks environmental scanning. Its advantage is the high quality of the product, and the third aspect is the strong sense of experience, the advantage of social media, and localized marketing. The disadvantages are high product positioning, fast store opening, and the pressure of financial chain management and supply chain management. However, in our survey, we also identified opportunities to expand online sales and mobile payments to maximize benefits in today's globalized world. However, despite Starbucks' growth prospects, its position is now precarious due to low coffee acceptance and threats from coffee brands such as Lucky Coffee. According to the analysis, Starbucks can improve its current weakness by strengthening its market power, expanding its strategy, differentiating its strategy, and adopting a reasonable and flexible pricing system.

About the use of machine learning in modeling business processes

In a highly competitive environment, as well as the activation of the domestic production market, enterprises need to quickly adapt to modern conditions. There is an obvious increase in the number of small manufacturing enterprises that participate in tenders on electronic trading platforms and offer their services to large enterprises, especially this growth is noticeable in the field of militaryindustrial complex. Customers prefer to cooperate with small enterprises that are adaptable to the order conditions and have not only short terms of order fulfillment, but also a flexible pricing system due to low administrative and bureaucratic costs. At the same time, such enterprises have problems with the organization of business processes when the volume of orders grows. In this paper, the authors have built a model of the Quality Control process using BPMN method on the basis of small enterprise practice. This model can be the basis for training a machine learning system to build a model of business processes. Natural language text processing is proposed as an area of artificial intelligence, which allows enterprises to use this unified technology to reduce the cost of developing and describing business processes.

Analysis of Brand Positioning in Online Course Companies to Change Consumption Patterns—A Case Study in the Personal Wellbeing Sector

This article examines the communication and marketing requirements of a prospective business enterprise that specializes in offering online courses focusing on psychology, personal growth and professional development to change patterns of educational production and consumption. The objective of this research is to analyse the necessary brand positioning for this company to improve its visibility, attracting and retaining interested customers. Using a sequential and evidence-based methodology, this study analyses the precise business requirements to establish an optimal and competitive platform for professionals offering wellbeing courses. This involved analysing the characteristics and needs of the target audience—the professionals who would deliver the courses—and the audience who would enrol in the courses. In addition, we assessed the company’s environmental context, its strengths, weaknesses and unique selling points, as well as effective marketing and positioning strategies, and its direct competitors. We identified a growing interest in online training of courses that contribute to wellbeing. Among the target audience, preferences were diverse, with 58.1% leaning towards personal growth, 45.9% interested in meditation and 43.2% in psychology. Social media, particularly YouTube (52.7%), served as the main source of information for these courses. Criticisms focused mainly on issues such as poor visual and audio quality (20%), inadequate structuring of content (30%) and perceived boredom (23.6%). Addressing these preferences through multilingual translation, niche targeting, diverse course offerings, flexible pricing and membership options can effectively cater to diverse customer segments. The findings emphasise the importance of prioritising audiovisual quality and personalised learning experiences to foster audience loyalty.

Hierarchical robust Day-Ahead VPP and DSO coordination based on local market to enhance distribution network voltage stability

As distributed energy resources (DER) are increasing, a variety of business models and markets are appearing. Business models such as virtual power plants (VPPs) contribute to enhanced stability of the power system while improving the profits of participating resources. However, the uncertainty of the behavior of DERs and the resulting stability issues are a major barrier to DER deployment and require a coordination framework between grid operators and business models to overcome. Therefore, in this paper, a hierarchical robust day-ahead coordination of a VPP and distribution system operator (DSO) based on the local market is proposed to improve the voltage stability of the distribution network by considering the uncertainty of DERs. For fairness reasons, the contribution of DERs to the distribution system can be addressed by a market-based approach. Local markets are divided into local energy markets (LEM) and local flexibility markets (LFM), which can consider the uncertainty and profitability of DERs. First, the DER determines the seller and buyer status of the LEM based on its self- scheduling with expected prices and is matched based on a double-auction mechanism. At this time, the worst-case scenario of load and renewable energy generation predicted by the Gaussian process (GP) is considered. The mismatched amounts in the LEM are aggregated by the VPP and bid into the wholesale energy market (WEM) operated by the TSO (Transmission system operator). Subsequently, DSO operates a LFM that coordinates microgrid (MG) and VPP on the distribution grid to increase voltage stability. The LFM and WEM problems are considered as interval optimization in the form of mixed integer linear programming and are applied together. The flexibility supply resulting from the adjustment of VPP is compensated by a loss-sensitivity-based flexibility price. Since voltage stability exists in upper and lower bounds, the upper and lower bound of net load through GP-based forecasting is considered along with the linearized network constraints. The results are validated through Monte-Carlo simulation-based scenarios on IEEE benchmark system in MATLAB environment. As a result, it is proved that the proposed model improves the distribution network voltage stability and the profit of the participants.

Understanding Post-Pandemic Surprises in Inflation and the Labor Market

Since the COVID-19 pandemic, the United States has experienced sharply rising then falling inflation alongside persistent labor market imbalances. This Economic Commentary interprets these macroeconomic dynamics, as represented by the Beveridge and Phillips curves, through the lens of a macroeconomic model. It uses the structure of the model to rationalize the debate about whether the US economy can expect a hard or soft landing. The model is surprised by the resiliency of the labor market as the US economy experienced disinflation. We suggest that the model's limited ability to capture this resiliency is a feature of using a linear model to forecast the historically unprecedented movements seen after the pandemic among inflation, unemployment, and vacancy rates. We explain how, by adjusting the model to mimic congestion in a tight labor market and greater wage and price flexibility in a high-inflation environment, as during the post-pandemic period, the model can then capture what has been a path consistent with a soft landing.

Incentivising peers in local transactive energy markets: A case study for consumers, prosumers and prosumagers

AbstractA decarbonised future grid should couple technological novelty with innovative market models to efficiently capture the value of grid‐edge decarbonised assets. The transactive energy (TE) concept inverts the centralised grid model by leveraging the evolution of consumers to prosumers to prosumagers. The principal TE market design challenge is transactive control—using market and pricing mechanisms to coordinate autonomous peer interactions, to optimally allocate power and incentivise peers. Peer attraction, incentivisation and retention are all critical for practical TE implementation along three adoption stages, starting from independent peer transactions with the centralised market; to decentralised peer coordination; towards distributed peer‐to‐peer trading. Addressing gaps in related scholarship, the authors investigate the economic positions of distinct peer roles in each adoption stage and two local pricing strategies. Using a real market dataset, trading decisions are simulated over a 1‐year horizon at hourly granularity. Coordinated action achieves better transactive control for the community, with economic superiority over centralised and distributed mechanisms. Distinct peer incentives should equitably align with their contribution to market functionality, such as the value ascribed to prosumagers' flexibility in local pricing and the constrained bargaining power of prosumers in distributed bilateral negotiations.

The Recent Trend for Marketing Mix in the Context of E-Commerce: A Literature Review

The influence of internet technology on all aspects of human life, and the convenience offered to customers by the e-commerce firms, in terms of flexibility in time and price, have raised the popularity of e-commerce in the world of business. This article aims to review the relevance of the traditional 4P marketing mix model in the era of digitalization, and discuss how it has been and can be modified to apply perfectly to the e-commerce industry. The pandemic also has caused a dramatic rise in online consumption, and the resulting changing trends in customers’ buying behaviour has reiterated the need for reviewing and reshaping the traditional marketing mix concept to adapt to the new business environment. The study elicits the conflicts that arise when the traditional marketing concepts are applied in the e-commerce environment. Starting from the traditional 4 P’s marketing mix, introduced by Jerome McCarthy in the 1960s, the article considers recent studies that outlined improved models for marketing, specifically in context with e-commerce, and identifies a plethora of factors and concepts in relation to e-commerce marketing. The involvement of science and technology makes the e-commerce industry very dynamic in nature. In addition, a crisis like the COVID-19 pandemic has led to drastic changes in the operation of businesses as well as the customers’ purchase behaviour in the last few years. Therefore, it is important to keep constructing new concepts and models that are compatible with the e-commerce industry.

NAVIGATING JUSTICE AND LEGAL EQUILIBRIUM IN AUTOMATIC PRICING ALGORITHMS: A CROSS BORDER LEGAL APPROACH

Automatic pricing algorithms with artificial intelligence (AI) technology in e-commerce have a significant impact on the running of the industry. This creates benefits as well as reaps polemics. Discrimination against consumers is one of them. For this reason, comprehensive treatment is needed to prevent negative impressions from occurring and can lead to the creation of justice and fairness. This research is normative qualitative research with the support of case and comparison approaches. The research results show that the algorithm uses AI to set prices based on market factors, production costs, and competition, providing price flexibility, price relevance, and increased business efficiency. Positive impacts include increased efficiency, price relevance, and consumer reach, while negative impacts involve the risk of discrimination and supervisory difficulties. Regulation and supervision are needed to maintain justice and legal balance. Unfair competitive practices, such as sudden price fluctuations, need to be monitored. Explicit regulations are needed to address the gap between AI developments and the existing legal framework. The implementation of automatic pricing algorithms must pay attention to aspects of justice and legal balance.

Prosumer Impact on Cellular Power Systems

This paper explores the impact of an increasing number of prosumers in electricity supply systems and investigates how market mechanisms can mitigate the negative effects. The Regional Energy Market Model simulates a supply system based on cellular structures, employing agent-based modeling to capture individual behaviors and simulate real market dynamics. This study includes various supply scenarios, such as a solely photovoltaic scenario and a technically diversified scenario with biogas-fueled combined heat and power units. For each scenario, fixed and flexible pricing scenarios are simulated to analyze their effects. The findings reveal that systems heavily reliant on photovoltaics experience negative effects at certain points due to seasonal limitations, while technically diversified supply scenarios demonstrate fewer drawbacks. Flexible pricing systems stimulate demand in a manner beneficial to the system, creating regional added value, and contributing to the balance between generation and consumption, depending on the supply scenario. However, the study underscores that economic incentives alone are insufficient for balancing generation and consumption. The results highlight the importance of exploring opportunities through the interplay of economic incentive mechanisms and technical possibilities.

Optimal unemployment insurance in a THANK model

We characterize optimal unemployment insurance (UI) in a heterogeneous-agent model with unemployment risk and sticky prices. In the long run, the optimal reform calls for a lower replacement rate that raises vacancies and lowers unemployment. In the short run, the optimal reform raises the replacement rate initially to smooth real wage adjustments along the transition and attenuate short-run welfare losses. Once at its optimal level, the replacement rate should vary counter-cyclically in response to demand shocks. Productivity shocks generate quasi-efficient fluctuations and call for a quasi-constant replacement rate. The aggregate welfare gains from an optimal reform are large, around 1% of equivalent consumption. The aggregate welfare gains from an optimal UI policy over the business cycle are smaller, around 0.2%, and essentially vanish with flexible prices because the aggregate demand stabilization motive is muted.

Competitiveness Strategy Analysis With SWOT Approach Of Grocery Stores Islamic Business Perspective

The grocery store became one of the UMKMs that channeled everyday needs to the community. This research aims to identify strategies to improve the competitiveness of food enterprises with a SWOT analysis approach, with a case study of Rizqi Halwa Kelontong Shop in Negarayu Village, Tonjong District, Brebes District. This research uses qualitative descriptive methods. Data sources in this research include primary and secondary data. With the collection of primary data from interview and observation, Secondary data from library studies such as journals and relevant articles. The strategy to compete in enterprise is the most crucial thing in development process of enterprise, so it requires the right strategy by implementing the SWOT analyst approach. Besides, as Muslim, also need to pay attention to existence of Islamic business ethics. Islamic business ethics teaches businessmen tobe able to follow orders they are taught and avoid prohibitions in accordance with Islamic rules. SWOT analysis of grocery stores shows strength in product completeness, price flexibility, and good customer service. However, there are weaknesses such as space constraints and SDM, a less strategic location. Opportunities to expand the product sector and enhance cooperation with suppliers need to be exploited, while threats come from large-store competition and price fluctuations. Strategies that match the SWOT matrix should used to maximize strengths, minimize weaknesses, and improve the competitiveness and resilience of retail stores in the market. The owner of this store applies the principles of Islamic business ethics and always keeps practicing shiddiq, trust, fathonah, and tabligh attitudes.

To commit or not? The impact of online reviews on retailers' price commitment strategy in competing supply chains

AbstractOnline reviews can effectively mitigate consumers' uncertainty about product valuations, thus affecting firms' pricing decisions. This paper develops a two‐period game model to investigate the impacts of online reviews on the retailer's price commitment strategies in two competing supply chains, each consisting of one manufacturer and one retailer. In the first period, the retailers strategically set prices and decide whether to commit to prices for their products. In the second period, the retailers adjust product prices in response to online reviews, if they choose not to commit to a price. We show that the retailers' price commitment strategies depend on consumers' perceived uncertainty about product valuations, the information value of online reviews and the unit misfit cost. Interestingly, the retailers can benefit from the information value of online reviews by implementing flexible pricing strategies. Furthermore, if the information value of online reviews is sufficiently high, both retailers will choose not to commit to a price in equilibrium. However, if the information value of online reviews is relatively low, the equilibrium in price commitment is asymmetric, that is, the retailer A commits to a price and its competitor chooses not to commit.