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Organizations have always faced the possibility of disruptions. Traditional approaches, such as shifting risks through insurance or improving organizational resiliency, view disruptions as threats. This study aims to propose a new perspective where disruptions can also be opportunities. By adopting project portfolio management (PPM), organizations can develop proactive capabilities to manage uncertainty and prepare to exploit future disruptions.

Drawing on publicly available research reports, company reports, professional standards and press reports, this study describes key features of PPM and provides detailed practical guidance on how to apply PPM in daily operations, especially in preparation for the next disruption.

The key steps in applying PPM in daily operations are: align portfolios and projects with strategic goals and objectives; establish a robust governance framework; optimize resource capability and capacity; build and implement appropriate implementation methodologies; continuously monitor, review and optimize the project portfolio; and develop a culture that embraces risks, innovation and adaptability.

This research has several limitations and implications. On limitations, the study was constrained by publicly available data, an in-depth interview with a consulting firm and a survey based on convenient sampling. These limitations will impact the generalizability of the findings. On implications, this paper shows how organizations can prepare for future disruptions by applying PPM. There are other ways to prepare for the unpredictable future, and further research is needed to explore other methods.

The results of this study have important practical implications for all organizations and in all sectors. Major disruptions are matters of “when,” not “how,” and responsible organizations need to pay attention. Based on the PPM discipline, this research provides an approach for business executives and project management practitioners to tackle this challenge. Furthermore, portfolio managers should use this information to promote and advocate for more disciplined planning to confront the uncertain future.

The findings of this paper carry important social implications. As the recent events showed the vastness of disruptions, from extreme heat to fires in Maui, sitting idly and waiting passively for an unpredictable future is not an option. This paper advocates the need for more awareness and preparation for future disruption by applying PPM. Furthermore, this research provides concrete guidelines for organizations and practitioners to consider as they confront the unknown. Additional research should investigate other effective strategies to meet the challenges of an uncertain and volatile future.

This study offers practical steps on how organizations may manage not only to survive but also to thrive in an uncertain and volatile world.

This paper aims to describe the product development process (PDP) of companies in the textile industry, seeking to understand the dynamics of their management from different actors along the production chain.

Qualitative empirical research adopted a multiple case studies design in five large Brazilian organizations, each representing a link in the production chain.

Textile PDP follows structured steps. However, it is still an informal process. The use of methodologies and tools for decision-making and control gates throughout the process is limited. Performance indicators do not cover all dimensions of the PDP since sales and profit are the main parameters for assessing projects. The predevelopment macro phase varies according to the product type and the company's business model, whereas the postdevelopment macro phase is nonexistent. PDP projects are executed through collective efforts of multiple departments in cross-functional teams, except for the commodities firms.

The study allows managers of Brazilian textile companies to understand the best practices in the PDP and those that require more attention, taking into account different business models and sectors of the production chain.

Our results contribute to the literature and practitioners by providing an overview of PDP management in the textile industry, covering its different production chain actors, types of projects and companies' characteristics.

Our result of this paper aims to indicate that the beta pricing formula could be applied in a long-term model setting as well.

In this paper, we show that the capital asset pricing model can be derived from a three-period general equilibrium model.

We show that our extended model yields a Pareto efficient outcome.

The capital asset pricing model (CAPM) model can be used for pricing long-lived assets.

Long-term modelling and sustainability can be modelled in our setting.

Our results were only known for two periods. The extension to 3 periods opens up a large scope of applicational possibilities in asset pricing, behavioural analysis and long-term efficiency.

Project portfolio benefit (PPB) evaluation is crucial for project portfolio management decisions. However, PPB is complex in composition and affected by synergy and ambidexterity. Ignoring these characteristics can result in inaccurate assessments, impeding the management and optimization of benefit. Considering the above complexity of PPB evaluation, this study aims to propose a refined PPB evaluation model to provide decision support for organizations.

A back propagation neural network optimized via genetic algorithm and pruning algorithm (P-GA-BPNN) is constructed for PPB evaluation. First, the benefit evaluation criteria are established. Second, the inputs and expected outputs for model training and testing are determined. Then, based on the optimization of BPNN via genetic algorithm and pruning algorithm, a PPB evaluation model is constructed considering the impacts of ambidexterity and synergy on PPB. Finally, a numerical example was applied to validate the model.

The results indicate that the proposed model can be used for effective PPB evaluation. Moreover, it shows superiority in terms of MSE and fitting effect through extensive comparative experiments with BPNN, GA-BPNN, and SVM models. The robustness of the model is also demonstrated via data random disturbance experiment and 10-cross-validation. Therefore, the proposed model could serve as a valuable decision-making tool for PPB management.

This study extends prior research by integrating the impacts of synergy and ambidexterity on PPB when conducting PPB evaluation, which facilitates to manage and enhance PPB. Besides, the structural redundancy of existing assessment methods is solved through the dynamic optimization of the network structure via the pruning algorithm, enhancing the effectiveness of PPB decision-making tools.

After reading and analyzing the case study, the students will be able to recognize the role of the mega environment in shaping business strategy, explore the challenges and opportunities in a mature industry (Foam), understand the business context of a family-owned firm and assess the implications and recommend managerial strategies.

In July 2019, Unifoam, a leading foam manufacturer, found itself at a crossroads as the company leadership grappled with diverging vision and future course of action. The newly appointed chief executive, Mr Faraz Khalid Shaikh, had overseen significant investments in expanding production capacity, and the time had come to reap the rewards. However, a series of unexpected events had unfolded, presenting the company with a unique set of challenges. Unifoam relied heavily on imported raw materials from China. Unifoam had high hopes of capitalizing on the opportunities presented by the China Pakistan Economic Corridor. However, the newly formed government had made significant policy changes regarding currency valuation and borrowing rates. This had increased the company’s working capital cost by 40%. This unexpected development had divided the board on the future direction and had forced the leadership to confront a crucial question: Should they hit the brakes or accelerate their growth strategies? This case study explored into the dynamic interplay between external factors, internal divisions and the family-owned nature of Unifoam. The analysis recognized the influence of the mega environment on the company’s strategy, exploring the challenges and opportunities within the mature foam industry and assessing the implications of conflicting approaches. This case study also offered valuable insights and managerial recommendations to guide the company’s path forward. Through embracing discomfort and confronting strategic dilemmas head-on, Unifoam sought to navigate uncharted waters and emerge as a resilient player in the evolving foam industry.

This is suitable for BBA or at the very start of MBA in the strategy courses, mainly business strategy and strategic management, and the case study can be positioned during the initial weeks in the course to provide a quick review of the basic analysis frameworks used in strategic decision-making.

Teaching notes are available for educators only.

CSS 11: Strategy.

Even though the end-user satisfaction construct has gained prominence as a surrogate measure of information systems performance assessment, it has received scant formal treatment and empirical examination in the data analytics systems field. In this respect, this study aims to examine the vital role of user satisfaction as a proxy measure of data analytics system performance in the financial engineering context.

This study empirically validated the proposed model using primary quantitative data obtained from financial managers, engineers and analysts who are working at Jordanian financial institutions. The quantitative data were tested using partial least squares-based structural equation modeling.

The quantitative data analysis results identified that technology quality, information quality, knowledge quality and decision quality are key factors that enhance user satisfaction in a data analytics environment with an explained variance of around 69%.

This empirical research has contributed to the discourse regarding the pivotal role of user satisfaction in data analytics performance in the financial engineering context of developing countries such as Jordan, which lays a firm foundation for future research.

In this study, we aim to investigate the connectedness spillovers among major cryptocurrency markets. Moreover, we also explore to identify factors driving this connectedness, particularly focusing on the sentimentality of total, short-term, and long-term return connectedness spillovers among cryptocurrencies under Twitter-based economic uncertainties and US economic policy uncertainty. Finally, we investigate the extent to which cryptocurrency markets serve as a safe haven, hedge, and diversifier from news-based uncertainties.

This study employs the connectedness approach following the combination of Ando et al. (2022) QVAR and Baruník and Krehlík's (2018) frequency connectedness methodologies into the framework proposed by Diebold and Yilmaz (2012, 2014). The data covered from November 10, 2017, to April 21, 2023, and the factors driving cryptocurrency connectedness spillovers are identified and examined. The sentimentality of total, short-term, and long-term return connectedness spillovers among cryptocurrencies, concerning Twitter-based economic uncertainties and US economic policy uncertainty, are analyzed. We apply the Wavelet quantile correlation (WQC) method developed by Kumar and Padakandla (2022) to explore the effects of Twitter-based economic uncertainties and US economic policy uncertainty on Cryptocurrency market connectedness risk spillovers. Besides, we check and present the robustness of WQC findings with the multivariate stochastic volatility method.

Our findings indicate that Ethereum and Bitcoin are net shock transmitters at the center of the connectedness return network. Ethereum and Bitcoin hold the highest market capitalization and value in the cryptocurrency market, respectively. This suggests that return shocks originating from these two cryptocurrencies have the most significant impact on other cryptocurrencies. Tether and Monero are the net receivers of return shocks, while Cardano and XRP exhibit weak shock-transmitting characteristics through returns. In terms of return spillovers, Ethereum is the most effective, followed by Bitcoin and Stellar. Further analysis reveals that Twitter economic policy uncertainty and US economic policy uncertainty are effective drivers of short-term and total directional spillovers. These uncertainty indices exhibit positive coefficient signs in short-term and total directional spillovers, which turn predominantly negative in different magnitudes and frequency ranges in the long term. In addition, we also document that as the Total Connectedness Index (TCI) value increases, market risk also rises. Also, our empirical findings provide significant evidence of Twitter-based economic uncertainties and US economic policy uncertainty that affect short-term market risks. Hence, we state that risk-connectedness spillovers in cryptocurrency markets enclose permanent or temporary shock variations. Besides, findings of the low value of long-term spillovers suggest that risk shocks in cryptocurrency markets are not permanent, indicating long-term changes require careful monitoring and control over market dynamics.

In this study, we find evidence that Twitter's news-based uncertainty and US economic policy uncertainty have a significant effect on short-term market risk spillovers. Furthermore, we observe that high cryptocurrency market risk spillovers coincide with periods of events such as the US-China trade tensions in January 2018, the Brexit process in February 2019, and the COVID-19 outbreak in November 2019. Next, we observe a decline in cryptocurrency market risk spillovers after March 2020. The reason for this mitigation of market risk spillover may be that the Fed's quantitative easing signals have initiated a relaxation process in the markets. Because the Fed's signal to fight inflation in March 2022 also coincides with the period when risk spillover increased in crypto markets. Based on this, we present evidence that the FED's communication mechanism with the markets can potentially affect both short- and long-term expectations. In this context, we can say that our hypothesis that uncertainty about the news causes short-term risks to increase has been confirmed. Our findings may have investment policy implications for portfolio managers and investors generally in terms of reducing financial risks.

Our paper contributes to the literature by examining the interconnectedness among major cryptocurrencies and the drivers behind them, particularly focusing on the role of news-based economic uncertainties. More broadly, we calculate the utilization of advanced methodologies and the incorporation of real-time economic uncertainty data to enhance the originality and value of the research, which provides insights into the dynamics of cryptocurrency markets.

In response to multiple disruptions, the purchasing supply management (PSM) function in construction supply chain management (CSCM) has gained prominence due to stakeholder pressures, dynamic market conditions and the need to adhere to complex sustainability, safety and health regulations and standards. However, there is a noticeable absence of empirical research on measuring and mitigating PSM vulnerabilities, especially considering the distinct challenges faced by large engineer-to-order project-oriented manufacturers. To address these issues, the purpose of this study is to develop and test a novel method to assist companies in construction supply chains in assessing and managing risks associated with sustainable procuring and sourcing materials.

Grounded in the literature gaps on construction PSM and a real case supply chain, the research uses the design science research (DSR) approach to develop an integrated method for assessing PSM strategies in this sector. The method integrates three essential purchasing dimensions: supply risks, profit impact and sustainability risks of materials, supported by nine subdimensions. Empirical validation took place within a multinational European construction company based in Denmark.

Findings from the supplier–buyer relationships confirmed that the developed method allows for the identification of the key components that significantly impact supplier–buyer relationships, profitability and sustainability. The research further suggests that construction supply chain managers and purchasing practitioners can use the proposed method to evaluate PSM, thus enabling them to make more informed decisions.

Through the utilization of the proposed artifact, construction companies can take a more proactive approach to address PSM uncertainties, thereby enhancing their competitiveness in dynamic construction supply chains.

The research contributes to bridging the theory and practice, providing valuable assistance for construction companies assessing and managing the PSM and supply risks within global construction value chains. This paper provides original insights for the CSCM, aiding in adopting competitive PSM strategies to improve overall supply chain performance.

In recent years, investing with robo-advisors has gained momentum and is seen as a simplifying approach for individual investors to participate in financial markets. This chapter contributes to a better understanding of the concept of a robo-advisory and its implications for private investors by discussing its past, present, and future. It explores key issues, like cost-efficiency, historical performance, and automation levels, based on research and industry insights. Moreover, this chapter examines a robo-advisor's benefits, limitations, and challenges, like behavioral biases, regulation, and risk profiling. Finally, the importance of the ongoing megatrends of AI and green investing is examined concerning a robo-advisory.

This paper aims to propose a methodology for assessing an optimal portfolio of investment instruments that minimise the social costs of decarbonising economic activity while improving the environmental objectives proposed in EU legislation.

The methodology defines the net social cost of decarbonisation related to a portfolio of four instruments: installation of solar PV and wind generation, thermal insulation of households and deployment of heat pumps. The social cost is minimised by restricting it to the minimum level of the targets proposed in the Spanish National Energy and Climate Plan to reduce greenhouse gas emissions, increase generation from renewable sources and reduce energy consumption. The empirical approach also includes differences between regions according to the expected effect for instruments.

The application of this methodology to the environmental objectives defined in the current Spanish National Energy and Climate Plan for 2030 concludes that it is clearly possible to reduce the social cost of decarbonisation while improving environmental performance through a reorientation of investment instruments. In this case, such a reorientation would be based on a minimisation of efforts in thermal insulation of households and a maximisation of measures aimed at the installation of heat pumps.

The paper proposes a novel methodology for a social cost assessment that improves the allocation of a portfolio of environmental instruments. This portfolio could be extended in further work to include instruments related to transport or support for industrial decarbonisation, such as the deployment of renewable hydrogen, among others.