Accurate demand forecasting is the cornerstone of a firm’s operations. The statistical system forecasts are often judgmentally adjusted by forecasters who believe their knowledge can improve the final forecasts. While empirical research on judgmental forecast adjustments has been increasing, an important aspect is under-studied: the impact of these adjustments over different time horizons. Collecting data from 8 business cases, retrieving over 307,200 forecast adjustments, this work assesses how the characteristics (e.g., size and direction) and accuracy of consecutive adjustments change over different time horizons. We find that closer to the sales point, the number of adjustments increases and adjustments become larger and more positive; and that adjustments, both close and distant from the sales point, can deteriorate the final forecast accuracy. We discuss how these insights impact operational activities, such as production planning.

We examine the incentives for a firm to provide non-truthful demand information under a two-company shipping collaboration. We analyze how distorted demand reporting impacts the logistics costs of each individual company in the collaboration and how this impacts the stability of the collaboration agreement. We find that when the cost allocation proportions are agreed ex-ante based on the reported demand, companies have an incentive to deflate their demand when simple cost allocation rules are used; only when the Shapley value is in place, companies have no incentive to distort their demand information. When the cost allocation proportions are calculated ex-post, based on realized demand, the truth-telling strategy is dominant when the Shapley value or an allocation rule based on the demand or stand-alone costs is in place.

The S&OP literature highlights the importance of integrating financial planning with S&OP. However, neither S&OP nor budgeting literature offer descriptive or prescriptive studies on this daily organizational reality. This paper provides a case study in a multi-national, detailing the relationship and reciprocating effects (positive and negative) between S&OP and budget.

Love is all around in the world of InsurTech today. Both large corporates and startups have observed and learned from what happened and is still happening in FinTech: disruptive innovation does not necessarily equal "bye bye traditional insurance companies". Not all large corporate insurance companies will disappear and startups will not rule the insurance world.

This paper reports on results for the well-known resource-constrained project scheduling problem. A branch-and-bound procedure is developed that takes into account all best performing components from literature, varying branching schemes and search strategies, using the best performing dominance rules and assembling these components into a unified search algorithm. A composite lower bound strategy that statically and dynamically selects the best performing bounds from literature is used to find optimal solutions within reasonable times. An extensive computational experiment is set up to determine the best combination of the various components used in the procedure, in order to benchmark the current existing knowledge on four different datasets from the literature. By varying the network topology, resource scarceness and the size of the projects, the computational experiments are carried out on a diverse set of projects. The procedure was able to find some new lower bounds and optimal solutions for the PSPLIB instances. Moreover, new best known results are reported for other, more diverse datasets that can be used in future research studies. The experiments revealed that even project instances with 30 activities cannot be solved to optimality when the topological structure is varied.

The concept of degrowth aims fundamentally at reducing material and energy throughput equitably, while questioning the desirability of further economic growth. In order to achieve this reduction of society’s throughput, radical changes in the ways goods and services are produced, distributed and used are required. In this think piece, concepts of consumer integration into the value creation process and (new) enabling technologies are discussed as possible constituting elements of alternative organizational models in a degrowth society. To date, collaborative value creation concepts, such as crowdsourcing and mass customization, have been discussed almost exclusively as business model patterns for companies in economies that are set to grow. The same applies to the assessment of (new) technologies, such as additive manufacturing, web-based user interfaces for co-creation, and other flexible production technologies that allow for collaborative and individualized production. Potential positive and negative effects of these concepts and technologies with regard to the objectives of degrowth are discussed in order to initiate a debate about the inclusion of CVC for the design of alternative organizational models that are in line with degrowth thinking. This think piece illustrates that several elements of collaborative value creation and its enabling technologies coincide with degrowth objectives but do not lead per se to their attainment. Thereby, a starting point for future (empirical) work in this area is generated.

This paper is an invited request to describe the main research challenges in the domain of resource-constrained project scheduling. The paper is split up in three parts. In today’s challenges, research endeavors that have received a significant, but still not enough, attention have been described. In tomorrow’s research challenges, some promising research avenues for future research have been given. Finally, in yesterday’s challenge, a research topic that started decades ago, is said to have still a huge potential in tomorrow’s research agenda. This paper does not intend to give a full literature overview, nor a summary of all possible research paths. Instead, it is inspired from the author’s experience in academic research and practical consultancy and it serves as a personal opinion on a non-exhaustive set of promising research avenues, rather than giving a full literature-based advice for future research directions.

The payments industry is facing its most radical change in decades. This is due to at least four change drivers — increased regulation, changing customer behaviour, technological innovation and new entrants. The sector faces increased competition from large established tech companies and small FinTech start-ups that are moving into the payments space. Based on the authors’ work with companies in the financial services industry and expert interviews, this paper identifies two distinct types of trends: those enhancing the existing payments system and those trying to build a completely new system. It is clear that a lot of the innovations focus on disintermediating the incumbent organisations. But how can these organisations best address these changes? Building on previous research the authors discuss four crucial capabilities for incumbents to master in an increasingly turbulent environment like the payments sector — designing superior customer experiences, setting up data-driven infrastructures, building multiparty collaborations and providing platform-based solutions. It is impossible for organisations to predict what will happen, but they will be better prepared for the road ahead by investing in these four capabilities.