Capacity constraints as a trigger for high growth

High-growth enterprises (HGEs) have a large economic impact but are notoriously hard to predict. Previous research has linked high-growth episodes to the configuration of lumpy indivisible resources inside firms, such that high capacity utilisation levels might stimulate future growth. We theorize that firms reaching critically high capacity utilisation levels reach a “trigger point” involving either broad-based investment in further growth or shrinking back to previous levels. We analyze EIBIS survey data (matched to ORBIS) which features a question on time-varying capacity utilisation. Overcapacity is a transitory state. Firms enter into overcapacity after a period of the rapid growth of sales and profits, and the years surrounding overcapacity have higher employment growth rates. Firms operating at overcapacity make incremental investments (e.g. capacity expansion, process improvements and modern machinery) rather than investing in R&D and new product development. We find support for the “fork in the road” hypothesis: for some firms, overcapacity is associated with launching into massive investments and subsequent sales growth, while for other firms, overcapacity is negatively related to both investments and sales growth.

Does capacity utilisation influence financial performance? A study of Indian public bus transport companies

PurposeThe objective of the paper is to get a better understanding of capacity utilisation (CU) in Indian public bus companies. More specifically, this paper would be measuring CU and identifying the drivers of the same. Finally, the influence of CU on the financial performance of Indian bus companies is examined.Design/methodology/approachThe study adopted data envelopment analysis (DEA) to measure the CU in Indian public bus companies. Truncated regression was used to identify the drivers of CU. Subsequently, the ordinary least squares (OLS) regression was used to analyse the influence of CU on Indian bus companies' financial performance. The period of study was from 2013 to 17.FindingsThe significant drivers of CU were fleet age, passenger lead and fleet utilisation. Additionally, it was found that CU had a significant positive influence on the financial performance of Indian public bus companies and a unit increase in unused capacity has led to an increase of 7% in the operating ratio of the bus companies.Practical implicationsGetting insights into CU, apart from technical efficiency, is of immense use to both public transport researchers and practitioners. Managers of public bus companies should be mindful of CU as it has a significant bearing on their financial performance.Originality/valueThis is the first study in public transport, which establishes the linkage between CU and financial performance. Besides, a modified measure of cost-efficiency has also been conceptualised in this study.

Market structure of short sea shipping in northeast Asia

Purpose Short-sea shipping (SSS) plays an important role in regional transportation networks by supporting regional trade and improving inter-modality. In particular, countries in north-east Asia, such as China, South Korea and Japan have been served well by local SSS services. While SSS markets in Northeast Asia (NEA) have been developed by bilateral routes with sub-markets, the market structure of each sub-markets varies depending on concentration and competition levels as well as government intervention. The purpose of this paper is to analyse the market structure of SSS markets in the Northeast Asia. Design/methodology/approach Herfindahl–Hirschman Index (HHI) and concentration ratio are adopted to measure the market concentration from 2013 to 2017 for SSS markets in NEA. Additionally, the balance between supply and demand is investigated by measuring the capacity utilisation factor (CUF) based on slot capacity. Findings The market structure in the NEA SSS markets is influenced by firms’ behaviour under different levels of governmental intervention. Shipping firms in a market with more governmental intervention in market entry tend to focus on balancing supply and demand rather than increasing market share, whereas firms in a market with less intervention (and more competition) tend to increase their market share by pursuing efficient capacity management. Research limitations/implications The period of data set is limited to 2013–2017. Furthermore, prices or revenue for specific routes are not available. Originality/value This paper sheds light on the market structure and behaviour of players in SSS market. In addition, the work has value to measure capacity utilisation based on slot capacity.

Value chain politicisation to boost rare earth supply

Significance Short-term factors combined to strengthen prices, including widespread flooding in China’s Sichuan province and low capacity utilisation among producers outside China. In the first two months of 2021, Chinese exports of rare earths rebounded by 28.8% year-on-year to 7,068 tonnes, although this was boosted by the low base of a demand slump in early 2020. Impacts Beijing has threatened to cut off supplies of refined rare earth products to US aerospace firm Lockheed Martin for trading with Taiwan. Norway may plan mining after finding polymetallic sulfides in its seabed containing high concentrations of lithium and certain rare earths. China also imports rare earths, and problems with shipping raw materials from Myanmar will exacerbate its rare earth shortages. US firm Energy Fuels is partnering with Neo Performance’s European operations to provide concentrates free of radioactive materials.

The Extent, Dynamics, and Potential Predictors of Technical Efficiency and Capacity Utilisation in Small-Scale Fisheries in Oman

This paper investigates the extent, dynamics, and factors influencing technical efficiency (TE) and capacity utilisation (CU) in small-scale fisheries (SSF) using a two-stage data envelopment analysis (DEA) approach covering the period 2010–2012. A considerable extent of boat-level technical inefficiency, capacity underutilisation and scale inefficiency were evident. On average, TE and CU levels under the constant returns to scale (CRS) and variable returns to scale (VRS) models declined over time. The TE and CU scores of 2010 remained unaltered with the addition of ‘fishing time’ as an input to the model. The proportion of boats with unitary scale efficiency (SE) decreased from 26 % in 2010 to 12 % in 2012. The underutilisation rates of the inputs ‘crew’ and ‘fishing time’ ranged from 15.5 % to 31.6 % and 15.8 % to 28.6 %, respectively. Among the species category, the extent of excess capacity was 70 % to 156 % and 47 % to 119 % under the CRS and VRS models, respectively. The second-stage DEA results indicated that the explanatory variables ‘fishing location’, ‘catch per unit of effort’ (CPUE), ‘fuel costs’ and ‘crew share’ significantly influenced CU under the CRS model. In contrast, the significant influence of subsidies and other operating costs were noted under the VRS model. For the TE case, ‘age’, ‘education’, ‘subsidy’ and ‘CPUE’ were found to be significant under the CRS and VRS models. Other significant variables were found in the study under CRS and VRS models. Finally, the results from the descriptive and empirical analysis under the two-stage DEA model are discussed together with policy implications.