Portfolio Planning Research Articles

Impact of accelerated review policy on portfolio planning of vaccine companies

BackgroundWith the introduction of the accelerated drug review policy in China, the clinical research and development time and the review and approval time of drugs have been shortened accordingly. Especially under the influence of the COVID-19 pandemic, the vaccine formulations released through the accelerated review policy are springing up, and the question of how the accelerated review policy affects the investment portfolio of vaccine enterprises has also attracted more and more attention.Aims and methodsThe article uses mixed-integer linear programming to develop a new model on portfolio planning for vaccine companies based on the accelerated review policy context. The model is constructed using the Gurobi extension class of .NET, and the investment decision is made and simulated by the Gurobi solver to investigate the portfolio planning decision of a vaccine company maximizing the net present value of its vaccine production portfolio with the increase of available capital over a 20-year time horizon.ResultsThe NPV under the accelerated review policy is significantly higher than the net present value under the standard review policy when the available capital exceeds RMB 900 million. And the difference between the two of them peaks at RMB 1.87 billion when the available capital is RMB 1.9 billion; break-even occurs about 1.3 years earlier in the accelerated review policy than in the standard review; and when the available capital is the same, firms in the accelerated review policy choose to produce four products earlier and make the decision to invest in facility construction earlier; scenarios in the accelerated review policy are not as sensitive to changes in model parameters as they are in the standard review.ConclusionThe accelerated review policy is effective in providing incentives for commercialisation. The results of this study will provide an effective reference for vaccine companies to make scientific portfolio planning under the accelerated review policy.

Illuminating the landscape of high-level clinical trial opportunities in the All of Us Research Program.

With its size and diversity, the All of Us Research Program has the potential to power and improve representation in clinical trials through ancillary studies like Nutrition for Precision Health. We sought to characterize high-level trial opportunities for the diverse participants and sponsors of future trial investment. We matched All of Us participants with available trials on ClinicalTrials.gov based on medical conditions, age, sex, and geographic location. Based on the number of matched trials, we (1) developed the Trial Opportunities Compass (TOC) to help sponsors assess trial investment portfolios, (2) characterized the landscape of trial opportunities in a phenome-wide association study (PheWAS), and (3) assessed the relationship between trial opportunities and social determinants of health (SDoH) to identify potential barriers to trial participation. Our study included 181529 All of Us participants and 18634 trials. The TOC identified opportunities for portfolio investment and gaps in currently available trials across federal, industrial, and academic sponsors. PheWAS results revealed an emphasis on mental disorder-related trials, with anxiety disorder having the highest adjusted increase in the number of matched trials (59% [95% CI, 57-62]; P < 1e-300). Participants from certain communities underrepresented in biomedical research, including self-reported racial and ethnic minorities, had more matched trials after adjusting for other factors. Living in a nonmetropolitan area was associated with up to 13.1 times fewer matched trials. All of Us data are a valuable resource for identifying trial opportunities to inform trial portfolio planning. Characterizing these opportunities with consideration for SDoH can provide guidance on prioritizing the most pressing barriers to trial participation.

How Does Optimize Peer to Peer Lending Investment

This research uses general data about loans in 5 Credit Grades A, B, C, D and E which can be obtained from the KoinWorks P2PL factsheet platform. The research results show that there are 4 combinations of funding assets in the calculation of the optimal portfolio of the Markowitz Model with the lowest risk preferences consisting of funding assets in Credit Grades A, B, D and E with an expected portfolio return of 24.29% for the year and 2.02. % for monthly and the best risk level in a year of 1.39% for annual and 0.11% for monthly. Meanwhile, in the optimal portfolio planning of the Markowitz model with sharpe ratio, there are 3 combinations of funding assets consisting of Credit Grades A, B and D which obtain an expected portfolio return of 18.29% in the current year and 1.52% in that month. and the level of risk. best in a year of 1.39% for this year and 0.48% for this month, and portfolio performance of 13.1.

Loan portfolio planning and financial performance of Savings and Credits Cooperatives in Uganda: Evidences from SACCOs in Rubirizi District, Western Uganda

Loan portfolio planning and financial performance of Savings and Credits Cooperatives in Uganda: Evidences from SACCOs in Rubirizi District, Western Uganda

Evaluation of tieback developments for marginal oil fields with timing flexibility

The average size of new oil discoveries on the Norwegian Continental Shelf (NCS) is steadily decreasing. As standalone developments are often not economically viable for marginal fields, tiebacks to existing production facilities are considered in many cases. At the same time, many production facilities in mature production areas have spare capacity due to depleted reservoirs. In this paper we evaluate tieback development concepts for a marginal field having the choice between two hosts with different characteristics. We develop a model that allows to (1) evaluate the tieback development concepts; (2) determine the optimal choice of host facility for the field operator; and (3) optimize the timing of development taking into account oil, gas price and CAPEX uncertainty using a real options approach. In order to be able to reflect how the capacity constraints of a host affects the production potential of the field over time, we incorporate a production optimization model as part of the methodology. We apply the model to a real case on the NCS. We identify characteristics that drive the optimal choice of hosts. Specifically, we show how lifetime extension, reduction of CAPEX and additional spare capacity individually and in combination affect the competitiveness of one host over another therewith, providing valuable insight for tariff negotiations and portfolio planning. Apart from that we find that timing flexibility is of high importance in case of high downside risk. This makes our approach particularly relevant for marginal oil field development which are often characterized by prominent uncertainties.

Enhancing the Accessibility of Text Data in Decision Making for Capability-based Planning Using Ontology: A Perspective of Semantic Compliance

Project introduction texts provide decision-makers with essential information for project portfolio planning. These free texts offer valuable information about how developing capabilities align with their strategic goals. Capability-based Planning (CBP) process is concerned with optimizing the project portfolio to realize the planning, engineering, and delivery of these capabilities. However, up to now, the research on enhancing accessibility to free text data in the CBP decision-making process through semantic modeling is limited, leading the CBP’s decision-makers to ignore the potential advantages of existing semantic modeling methods when dealing with many free texts. This paper aims to address this gap by introducing knowl­edge modeling and mining of project introduction text corpus, leveraging semantic technology to support CBP. First, we design an ontology of capability to describe the core concepts relevant to the CBP process. Subsequently, a semantic framework based on the RDF knowl­edge graph is proposed, enabling humans and machines to comprehend project description texts. To capture the semantic data essential for CBP, a motif structure is employed to model semantic expressions, ensuring their consistency with CBP concepts through compliance checks. Finally, the effectiveness of the proposed semantic framework is evaluated by querying the project’s knowl­edge graph after semantic normalization, providing an assessment of its potential in CBP applications.

Enrollment forecast for clinical trials at the portfolio planning phase based on site-level historical data.

An accurate forecast of a clinical trial enrollment timeline at the planning phase is of great importance to both corporate strategic planning and trial operational excellence. The naive approach often calculates an average enrollment rate from historical data and generates an inaccurate prediction based on a linear trend with the average rate. Under the traditional framework of a Poisson-Gamma model, site activation delays are often modeled with either fixed initiation time or a simple random distribution while incorporating the user-provided site planning information to achieve good forecast accuracy. However, such user-provided information is not available at the early portfolio planning stage. We present a novel statistical approach based on generalized linear mixed-effects models and the use of non-homogeneous Poisson processes through the Bayesian framework to model the country initiation, site activation, and subject enrollment sequentially in a systematic fashion. We validate the performance of our proposed enrollment modeling framework based on a set of 25 preselected studies from four therapeutic areas. Our modeling framework shows a substantial improvement in prediction accuracy in comparison to the traditional statistical approach. Furthermore, we show that our modeling and simulation approach calibrates the data variability appropriately and gives correct coverage rates for prediction intervals of various nominal levels. Finally, we demonstrate the use of our approach to generate the predicted enrollment curves through time with confidence bands overlaid.

Risk-based portfolio planning of dike reinforcements

A system of dikes in flood-prone areas continuously requires measures to mitigate changes such as ageing and climate change. Planning costly measures requires proper insight into system risk effects. Especially in a riverine dike system, the risk contributions of individual assets to the system flood risks are not independent, because reinforcement of a dike upstream increases the risks downstream. Tactical plans define the planning of consecutive measures to implement a flood risk reduction strategy, which may take decades. They may differ due to choices such as a prioritization metric, planning conditions and budget. In this study, a method is developed to compare different tactics to prioritize and plan measures in interdependent systems of dikes to reduce risks most effectively and efficiently. A case study meant as a proof of concept was carried out for the reinforcement of about 500 km of dikes along the Rhine River branches in the Netherlands. We studied the effects of 12 different tactical plans on the aggregated risks over time. The economic risks differ by up to about 40%, and the risks on victims differ by up to 70 %. We conclude that tactical planning and corresponding decisions are important for reduction of time-aggregated flood risks.

Theoretical Fundamentals of Scaled Business Agility and Project Portfolio Management at Automotive Manufacturers

This study has the aim to explain the theoretical fundamentals of scaled agile business structures and of the traditional project portfolio management before laying out the discrepancies of agility with project portfolio management at large enterprises such as automotive manufacturers.&#x0D; For the exploration of the scarcely addressed topic of agility at portfolio level, current journals were mainly consulted. Further, for the theoretical exposition of project portfolio management, current journals and textbooks about business strategies and project management were used as well as journals for information about portfolio management.&#x0D; As a result of this paper, it was found that the difference of agile delivery to the traditional organization is the focus on small work packages instead of detailed long -term planning. When focusing on smaller work packages, portfolio planning becomes more iterative and bottom-up ideas have a higher impact on program level. &#x0D; For other industries then automotive manufacturers, other company sizes, or even other automotive manufacturers, which are built from the ground up to be more agile, the findings of this paper are not relevant.

A performative perspective on sensing, seizing, and transforming in small- and medium-sized enterprises

ABSTRACT This study investigates organizational sensing, seizing, and transforming, which are critical activities in developing and exercising dynamic capabilities (DCs)––an organization’s capacity to reconfigure its resources in response to a changing environment. Previous research on small- and medium-sized enterprises (SMEs) has predominantly focused on well-established business processes that are considered functional DCs, including product development, portfolio planning, and customer management, highlighting their role in facilitating resource reconfiguration. However, these studies implicitly assume the existence of functional DCs, without explaining what contributes to their development. We build on recent theoretical arguments emphasizing the performative dimensions of the DC construct and examine how SME practitioners sense and seize opportunities and threats, and subsequently transform their resources and operations. Our findings highlight a series of practices employed in ongoing social interactions to develop functional DCs or reconfigure established routines. These practices are situated in social interaction contexts characterized by distinct modes of communication, including resonance, generativity, and call for action. By offering a communicative explanation of the performance and dynamization of sensing, seizing, and transforming, this study underscores the pivotal role of interpersonal dynamics in facilitating resource reconfiguration.

Project Portfolio Planning Taking into Account the Effect of Loss of Competences of Project Team Members

This paper deals with a declarative model of the performance of employees conducting variably repetitive tasks based on the assumption of aging competences. An analytical model is used to consider refreshing the competences of the team’s multi-skilled members and shaping the structure of staff’s competences to maximize their mutual substitutability in processes typical for a multi-item lot-size production. Its impact on maintaining the skill level of employees is important in cases of an unplanned event, e.g., caused by employee absenteeism and/or a change in the priorities of orders carried out, disrupting the task of software companies. The developed model implemented in the constraint programming environment enables the formulation of decision-making versions of both the problem of analysis (seeking an answer to the question to discover whether there is a solution that meets the given expectations) and synthesis (seeking an answer to the question, assuming there is a solution that meets the given expectations). The potential of the proposed reference model-based approach is illustrated with examples.

An improved probability-based discrete particle swarm optimization algorithm for solving the product portfolio planning problem

Product Portfolio Planning (PPP) is one of the most critical decisions for companies to gain an edge in the competitive market. It seeks for the optimal combination of products and attribute levels offered for customers in the target market, which is a NP-hard combinatorial optimization problem. In this paper, a Probability-based Discrete Particle Swarm Optimization (PDPSO) algorithm is proposed to solve the PPP problem. In PDPSO, the particle is encoded as discrete values, which can be straightforwardly used to represent the product portfolio with discrete attributes. PDPSO adopts a probability-based mechanism to update particles. Specifically, a probability vector is used to decide the probability of three search behaviors, i.e., learning from the personal best position, global best position, or random search. In experiments, the search performance of PDPSO has been compared with that of a Genetic Algorithm (GA) and a Simulated Annealing (SA) algorithm on generated PPP problem cases with different sizes. The results indicate that PDPSO obtains significantly better optimization results than GA and SA in most cases and obtains desirable/near-optimal solutions on various PPP problem cases. A case study of notebook computer portfolio planning is also presented to illustrate the efficiency and effectiveness of PDPSO.

Multi-scale planning model for robust urban drought response

Increasingly severe droughts are straining municipal water resources and jeopardizing urban water security, but uncertainty in their duration, frequency, and intensity challenges drought planning and response. We develop the Drought Resilient Interscale Portfolio Planning model (DRIPP) to generate optimal planning responses to urban drought. DRIPP is a generalizable multi-scale framework for optimizing dynamic planning strategies of long-term infrastructure deployment and short-term drought response. It integrates climate and hydrological variability with high-fidelity representations of urban water distribution, available technology options, and demand reduction measures to yield robust and cost-effective water supply portfolios that are location-specific. We apply DRIPP in Santa Barbara, California to assess how least cost water supply portfolios vary under different drought scenarios and identify portfolios that are robust across drought scenarios. In Santa Barbara, we find that drought intensity, not duration or frequency, drives cost increases, reliability risk, and regret of overbuilding infrastructure. Under uncertain drought conditions, a diversified technology portfolio that includes both rapidly deployable, decentralized technologies alongside larger centralized technologies minimizes water supply cost while maintaining high robustness to climate uncertainty.

TOOLS FOR INCREASING THE COMPETITIVENESS OF ENTERPRISES USING MARKETING COMMUNICATIONS

The general composition of the marketing toolkit of enterprises is summarized. The goal of the study was the formation of tools for increasing the competitiveness of agricultural enterprises by means of marketing communications. The place of marketing communications of enterprises in the general system of the marketing mix is shown. The general criteria of competitiveness of agricultural enterprises are outlined. The directions and means of using marketing communications in order to strengthen the competitiveness of agrarian business entities have been determined, in particular by groups: (1) dissemination of communication and research policy, (2) communications in the field of product and market portfolio, (3) financial and resource planning of communications, (4) development of strategic market communications. The factors of the development of processes of interpretation of the information received by users are determined. It has been established that the competitiveness of an agricultural enterprise is a complex system category that gives a comprehensive description of its ability to oppose direct competitors, both at the current time and in the strategic perspective, in the target market segment where the enterprise’s products are positioned, in order to ensure the functioning and planned development under the pressure of competition and the action of factors and conditions of the business environment. A structural and functional model for improving the policy of ensuring the competitiveness of agricultural enterprises has been developed. An arsenal of tools for increasing the competitiveness of enterprises in the agrarian sector of the national economy by means of marketing communications has been developed.

A Multistep Iterative Ranking Learning Method for Optimal Project Portfolio Planning of Smart Grid

Optimal project portfolio planning is a typical nonconvex, multiobjective, highly constrained, multitemporal coupling, and combinatorial optimization problem. This paper proposes a novel multistep iterative ranking learning method (MIRL) to solve this complex combinatorial optimization problem from massive infrastructure projects of smart grid. The optimal project portfolio planning problem of power grid is formulated as the optimization process of massive project priority sorting with an improved knapsack model. The proposed method dynamically optimizes the best infrastructure project combination for each round to maximize the economic, social, and security benefits without exceeding the annual investment limit. A pairwise-based ranking learning algorithm is used to mine the priority sorting law from massive historical combination data of power grid to initialize candidate project portfolio. In order to approach the optimal portfolio planning solution with the constraint satisfactions of project construction duration and electric load supplies, a heuristic greedy strategy is designed to search the solution dynamically for selecting the project having highest construction benefits iteratively. The effectiveness of the proposed method is proved by experiments with real-world project data of Hunan power grid in China, and experimental results show that the proposed MIRL can outperform other methods on investment efficiency, calculation time, and rationality of project construction period schedule.

Implementation of Portfolio Assessment in English Lessons at MAN Insan Cendekia Jambi

This research aims to: 1) obtain an overview of portfolio assessment planning for English language learning at MAN Insan Cendekia Jambi, 2) describe the implementation of portfolio assessment for English language learning at MAN Insan Cendekia Jambi. 3) describe the advantages and obstacles of portfolio assessment in English language learning at MAN Human Cendekia Jambi. The approach used in this research is qualitative research. The results of the research show that portfolio assessment planning in English language learning at MAN Insan Cendekia Jambi includes several components, such as: educator preparation, consideration of the values that will be applied, and determining appropriate learning material. Apart from that, the assessment also includes students' affective aspects which aim to form good student attitudes in accordance with the Islamic boarding school concept. The implementation of portfolio assessment in English language learning also experiences obstacles, namely limited time, different student characteristics, and institutional support regarding portfolio assessment that is not yet well systemized. Portfolio assessment in English language learning at MAN Insan Cendekia Jambi includes: evidence of thought processes, quality of activities, and diversity of approaches.The implementation of portfolio assessment in English lessons at MAN Insan Cendekia Jambi shows the school's commitment to improving students' learning experience holistically. This research has the potential to provide new insights regarding the effectiveness of alternative evaluation methods in the context of English language education.

TOOLS FOR INCREASING THE COMPETITIVENESS OF ENTERPRISES USING MARKETING COMMUNICATIONS

The general composition of the marketing toolkit of enterprises is summarized. The goal of the study was the formation of tools for increasing the competitiveness of agricultural enterprises by means of marketing communications. The place of marketing communications of enterprises in the general system of the marketing mix is shown. The general criteria of competitiveness of agricultural enterprises are outlined. The directions and means of using marketing communications in order to strengthen the competitiveness of agrarian business entities have been determined, in particular by groups: (1) dissemination of communication and research policy, (2) communications in the field of product and market portfolio, (3) financial and resource planning of communications, (4) development of strategic market communications. The factors of the development of processes of interpretation of the information received by users are determined. It has been established that the competitiveness of an agricultural enterprise is a complex system category that gives a comprehensive description of its ability to oppose direct competitors, both at the current time and in the strategic perspective, in the target market segment where the enterprise’s products are positioned, in order to ensure the functioning and planned development under the pressure of competition and the action of factors and conditions of the business environment. A structural and functional model for improving the policy of ensuring the competitiveness of agricultural enterprises has been developed. An arsenal of tools for increasing the competitiveness of enterprises in the agrarian sector of the national economy by means of marketing communications has been developed.

Research on the Application of Mean-Variance Model in Securities Investment Portfolio Planning: Evidence from China Stock Market

Research on the Application of Mean-Variance Model in Securities Investment Portfolio Planning: Evidence from China Stock Market

Electricity generation portfolio planning and policy implications of Turkish power system considering cost, emission, and uncertainty

Türkiye is the fastest-growing energy market among the OECD members, and it is among the world's top 20 energy-consuming countries. The existing electricity generation capacity of Türkiye has doubled in the last decade. Planning the electricity generation portfolio is an important problem for the decision and policymakers, especially in terms of sustainable development, and it is crucial for Türkiye's economic growth. In this paper, we study the long-term electricity generation portfolio optimization while considering the uncertainties. An optimization algorithm is modeled and solved while integrating uncertainty information as part of the Pareto concept. The results of three scenarios are presented and policy implications are discussed and compared with similar Turkish case studies and government projections. The results suggest that it is less risky to minimize emissions, thus, more likely to be sustainable than to minimize costs. Comparisons among solutions show that nuclear is a substitute for renewable resources and comparisons among other studies show that natural gas and hydro are substitutes for each other. Multi-objective formulation reveals that the government's scenario provides favorable results in business-as-usual conditions; however, nuclear and renewable investments that the government has planned are too ambitious to keep costs lower while decreasing emissions.

A 2-phase interdependent methodology for sustainable project portfolio planning in the pharmaceutical industry

In response to the increasing awareness of sustainability issues, companies have reevaluated their approach to research and development (R&D). Taking into account the long-term effects and consequences of R&D projects on social, economic, and environmental conditions, this research has presented a comprehensive methodology for planning pharmaceutical holding company project portfolios by considering both sustainability dimensions and profitability objectives. The first phase of the developed methodology consists of a new combined MCDM method that is used to determine the sustainability score of each project. The following phase focuses on developing a bi-level bi-objective optimization model that is designed to take into account the decentralized structure of pharmaceutical holdings to optimize the budgeting, selection, and scheduling of projects. This optimization model proposes that the head office of the holding company as leader allocates R&D budgets between subsidiaries as followers to maximize the holding company's profit and sustainability. In contrast, the followers are responsible for selecting and scheduling research projects. We examine the optimal strategy of each actor using an illustrative case to validate the methodology. Based on experimental results, an approach focusing on sustainability versus profitability (or vice versa) has a significant impact on decisions made at each level of operation. The results reveal that the proposed approach can be adopted by the holding companies to improve the performance of portfolio planning from the sustainability perspective.