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The purpose of this report was to evaluate the effectiveness and practicality of system dynamics modeling in integrating econometric equations to describe the effects of supply chain material and information delays on pricing decisions and consequent financial results in an animal feed export business.

An empirical dynamic model, loaded with econometric theory of price effect on competitive demand, was used to describe the input data.

The model simulation outputs proved themselves relevant in analyzing the complex interconnections of multiple variables affecting the profitability in a commercial routine, supporting the decision process among sales managers. The impact of information delay on price decisions and business financial results were estimated using the model proposed.

This paper describes an empirical model, based on system dynamics, that predicts operating contribution margins and cash conversion cycles based on estimation of information and material delays in a supply chain. The method is pragmatic and simple for business routine implementation.

Professionals from the dairy sector commonly believe that the results of Global Dairy Trade (GDT) auctions are a good leading indicator for prices of dairy commodities. The purpose of this paper is to test that hypothesis for prices of key dairy commodities (skimmed milk powder (SMP), whole milk powder (WMP), butter and cheddar) in the main dairy markets (the US, EU and Oceania).

The leading properties of the GDT auctions are investigated using vector error correction models (VECM).

The results show that prices at GDT auctions may be treated as a benchmark for global prices of WMP and SMP as they affect prices in all considered markets. However, in case of EU market the relationship with the GDT is bidirectional. GDT prices reveal some leading properties also in cheddar market, however price relationships in this market are much more complex. In case of butter market, GDT can be regarded as a benchmark only for Oceania.

The results of this paper improve knowledge on price transmission in dairy markets, show the role of the GDT auctions in the price setting process, and thus may help professionals from the dairy sector to formulate their price expectations more precisely.

Despite the fact that many professionals from the dairy sector treat GDT auctions as a benchmark, so far their leading properties have not been scientifically proven.

Agricultural aggregation schemes provide numerous farmer-facing benefits, including reduced transportation costs and improved access to higher-demand urban markets. However, whether aggregation schemes also have positive food security dimensions for consumers dependent on peri-urban and local markets in developing country contexts is currently unknown. This paper aims to narrow this knowledge gap by exploring the actors, governance structures and physical infrastructures of the horticultural value chain of Bihar, India, to identify barriers to using aggregation to improve the distribution of fruits and vegetables to more local market environments.

This study uses mixed methods. Quantitative analysis of market transaction data explores the development of aggregation supply pathways over space and time. In turn, semi-structured interviews with value chain actors uncover the interactions and decision-making processes with implications for equitable fruit and vegetable delivery.

Whilst aggregation successfully generates multiple producer-facing benefits, the supply pathways tend to cluster around urban export-oriented hubs, owing to the presence of high-capacity traders, large consumer bases and traditional power dynamics. Various barriers across the wider enabling environment must be overcome to unlock the potential for aggregation to increase local fruit and vegetable delivery, including informal governance structures, cold storage gaps and underdeveloped transport infrastructures.

To the best of the authors’ knowledge, this study is the first critical analysis of horticultural aggregation through a consumer-sensitive lens. The policy-relevant lessons are pertinent to the equitable and sustainable development of horticultural systems both in Bihar and in similar low- and middle-income settings.

This paper aims to investigate whether developers’ ask lower prices on homes in redevelopment sites than they do on similar units in smaller developments completed over a shorter time span. It also investigates whether developers price units differently at different stages of the redevelopment process. The development of designated redevelopment areas often consists of multiple projects spread across several years, some in parallel, some sequential. New units are put on the market in a piecemeal fashion, and infrastructure, shared green spaces and shared facilities are installed successively.

A hedonic price model is used to analyse sales prices of 7,000 new apartments in Oslo sold between 2011 and 2015, all else being equal. The paper distinguishes between infill as one-stage projects, and multi-staged competitive and multi-staged monopolistic redevelopments.

Dwellings in redevelopment projects sell at a lower price than similar dwellings in infill projects. In competitive redevelopments, those in charge of the last projects put a slightly higher price on apartments. In redevelopments involving only one developer, the last stages ask the lowest prices.

This research expands our understanding of developers’ pricing behaviour. Developers supplying housing for the private market through redevelopments land are willing to take risks particularly in the initial stage.

The findings indicate that credit institutions financing developers’ projects need to take into account the structure of selling prices, including lower prices and higher risk of pursuing redevelopment projects.

Gaining a better understanding of developers’ pricing behaviour deepens our insights into the dynamics of market-led urban brownfield developments; this knowledge may moreover inform policies on sustainable urban growth.

An original investigation of housing transactions in urban brownfield sites in Oslo provides fresh insights into developers’ pricing behaviour.

In the shipping industry, both sales and purchases of second-hand ships and freight transport services are prevalently tailormade and traded with intense bilateral negotiations. Price bargaining is the key step of this negotiation process and plays a crucial role in determining mutually agreed prices. Despite its cruciality and applicability, the price bargaining has yet received due conceptual and/or theoretical attention in the shipping literature. This paper attempts to conceptually examine the role of bargaining in shipping transaction prices and subsequently puts forward directions for future research. In doing so, the paper focuses on two types of transactions taking place in shipping markets: asset market trading of second-hand vessels and service market trading shipping freights.

The paper begins with a systematic literature review of price bargaining in the field of economics and management disciplines from a game-theoretic perspective. This approach does logically lead to the establishment of a conceptual framework for price bargaining in shipping sub-markets as a step toward having taken into consideration a variety of heterogeneities commonly present in trading activities and market dynamics.

A set of research areas has been consequently identified where price bargaining and mechanisms for the shipping freight and asset markets could be further explored and analyzed in a way to make better pricing decisions under a more tangible framework.

One of the critical challenges when using bargaining mechanisms to make a decision on pricing shipping services and assets is how to operationalize the study for empirical investigation as some of the factors are internal information of the players and are not adequately revealed to externals: that is, an imperfect information sharing case. The current study aims, however, not to conduct an empirical analysis but to initiate a conversation among maritime economists by bringing their attention to this not-yet fully explored and potentially impactful field of research and by asking them to treat bargaining from a perspective for pricing shipping assets and services. It is claimed that, by doing so, one could better understand price differences between individual contracts.

This study would be considered the first of its kind to provide a detailed survey of the bargaining theory and models from a game theoretical perspective as a theoretical lens to understand its importance and relevance in pricing shipping assets and services. It also provides a simplified operational case on utilizing bargaining in practically pricing freight services.

Predicting the stock market's prices has always been an interesting topic since its closely related to making money. Recently, the advances in natural language processing (NLP) have opened new perspectives for solving this task. The purpose of this paper is to show a state-of-the-art natural language approach to using language in predicting the stock market.

In this paper, the conventional statistical models for time-series prediction are implemented as a benchmark. Then, for methodological comparison, various state-of-the-art natural language models ranging from the baseline convolutional and recurrent neural network models to the most advanced transformer-based models are developed, implemented and tested.

Experimental results show that there is a correlation between the textual information in the news headlines and stock price prediction. The model based on the GRU (gated recurrent unit) cell with one linear layer, which takes pairs of the historical prices and the sentiment score calculated using transformer-based models, achieved the best result.

This study provides an insight into how to use NLP to improve stock price prediction and shows that there is a correlation between news headlines and stock price prediction.