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The 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.

The 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.

The 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.

Getting 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.

This 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.

The purpose of this paper is to eliminate the wastes and inefficient procedures in the maintenance organization of aircraft so as to reduce its downtime and increase mission availability.

Customized lean Six Sigma (LSS) was applied at the task level and servicing cycle level to reduce the task content, cycle length and resources in servicing. The loading of the servicing facility was simulated through a simulation program developed from a statistical analysis of historical data for validating/simulating/determining optimum loading of servicing facility with refined tasks, reduced cycle length and resources. In simulation, the optimum combination of manpower, resources and infrastructure at the facility level was determined through sensitive analysis and design of experiments (DoE).

Optimization at the task level and its re-organization at the servicing cycle level reduced the cycle length by 55-68 per cent and manpower resources by 26 per cent. This further reduced facility-level manpower by 25 to 40 per cent, capacity requirements by more than 33 per cent and annual aircraft downtime by 78 per cent. The approach reduced the average number of aircraft undergoing servicing at each airbase at any time from 2.35 to just 0.76 and increased the mission availability to 20 per cent.

The hallmark of the paper has been the design of LSS approach from structured historical data and its validation through innovative simulation. The multi-pronged bottom-up approach practically bundles all wastes resident in the maintenance organization. The paper provides cursory approach to lean practitioners in the elimination of wastes in the maintenance of capital assets like aircraft.

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.

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.

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.

The period of data set is limited to 2013–2017. Furthermore, prices or revenue for specific routes are not available.

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.

The life span of an aircraft is usually around 30 years in the commercial aviation industry. During this time span, aircraft needs maintenance to stay in service. The cost of maintenance, repair and overhaul (MRO) activities in its pure nature is a significant portion of operations, accounting around 10 percent of all cost drivers. The purpose of this paper is to design/develop and critically assess a comprehensive model of operations at Turkish Technic – the MRO department of Turkish Airlines.

A comprehensive systems dynamics model is designed and developed to holistically represent and critically assess the different facets of MRO operations to help in analyzing various decision scenarios at Turkish Airlines.

The developed system dynamics (SD) model presented unique opportunities to test various MRO operations’ work load and aircraft fleet expansion policy alternatives. The model can also be used as a “learning laboratory” by altering various system parameters and testing different policies. The case study results suggested that MRO operations have a direct impact on the available number of airworthy aircrafts and hence, the usable fleet seat capacity; to sustain a profitable airline fleet, the airline companies should take into account the unique characteristics/needs of MRO operations for both existing and new/prospective aircrafts.

There are several SD studies in the literature focusing on the airline industry, but the MRO operations are virtually neglected in them. Hence, the proposed SD model contributed to the extant literature. The value of the developed model stems from its potential use in the critical analysis of decision scenarios as well as being leveraged as a training/learning laboratory.

As the rise in expenditures will be even faster when the baby-boom generation soon reaches healthcare-dependent ages, healthcare providers are facing cost management decision of achieving superior performance. Taiwan provides a unique environment that the dialysis service providers face only one medical buyer. The purpose of this paper is to discuss cost factors of dialysis facilities.

This study provides a comprehensive analysis of factors influencing the dialysis costs using the data collected from a large renal clinic chain at Taiwan. The multiple linear regression analysis is employed to examine the factors influencing dialysis costs. The research sample composed of 1,255 patients is collected from 16 dialysis centers in Taiwan.

The results indicate that the treatment costs of dialysis are influenced by managerial factors including capacity utilization rate (CUR), the percentage of shares held by the owners and the geographical location of clinics (LC). The findings assist renal clinics to identify the parts critical to the cost control. Our results indicate that medical variable costs for performing the dialysis treatments are significantly influenced by such managerial factors as CUR, the percentage of owners’ shares holding and LC.

By identifying a comprehensive set of costs drivers for dialysis services, this study provides useful information for both health providers and policy makers. In specific, the result assists these providers to consider the utilization of better mechanisms/instruments to control costs by increasing the operational efficiency and achieving the economies of scale.

This paper contributes to exploring costs drivers that are generally absent from the extant literature. The result suggests that the regulators should be aware that the dialysis providers may reject costly patients. Hence, to establish the appropriate monitoring mechanisms to prevent such incidence is important. Finally, many other countries in addition to Taiwan also have a similar practice as national health insurances or services (e.g. Medicare in the USA or National Health Service in the UK). Those health systems may all face a similar cost control issues for handling end-stage renal disease patients. The analysis can help health systems worldwide to better design the reimbursement rates to account for the differences existed in dealing with the dialysis treatment costs.

OUT of 21 centres set up by the Government in 1965 to help industry adopt automation and, later, the use of robots, 11 have already closed through lack of support. Another, that in Birmingham, is very likely to cease its work very shortly. The cause, mainly, is lack of support from the industries they were formed to help

Unlike manufacturing firms where the production of goods can be adjusted according to the demand of customers, hospitality firms do not have the ability to alter the capacity of the changing demand of guests in a short period of time. Given the relatively fixed capacity or supply, maximizing revenue through inventory control is essential for hospitality operations. This chapter covers operations inventory control extracted from the field of revenue management. First, the concept of capacity management and planning is enclosed and various capacity management tactics and inventory control strategies are explored. Next, the management and principles of space inventory through inventory-based restrictions, strategic pricing, displacement analysis, and distribution channel management are addressed. Finally, the respective applications of these principles, strategies, and tactics in several hospitality sectors are discussed.

The neo-Kaleckian model follows the ideas of Marx, Keynes and Kalecki, that investment is a key influencing factor in the dynamics of the capitalist mode of production. Through the discussion of different forms of investment decision function, this paper constructs the analysis framework of wage-led and profit-led economic growth regimes.

The model has become an important theoretical paradigm for current Western heterodox economists regarding the research on the impact of functional income distribution on economic growth, and it has a very large impact on both theoretical and empirical research. Starting from Marx's reproduction theory, this article discusses the theoretical shortcomings of the neo-Kaleckian growth regime model.

This paper mainly focuses on three aspects: (1) the ideological legacy of “Smith's Dogma”; (2) neglecting the restrictions on income distribution from the organic composition of capital and the surplus value rate; (3) technological progress and the formation of a new long economic wave.

The authors believe that the neo-Kaleckian model unilaterally emphasizes the demand-side factors in the economy and, unconsciously or not, ignores the role of the supply-side, which makes it encounter certain limitations in explaining long-term growth. Even if some empirical conclusions are employed to bridge functional income distribution and technological progress, there is still a lack of a theoretical basis for accurately describing long-term economic changes using this model. In order to better promote high-quality economic development and accelerate the formation of a new pattern of economic development in which the domestic large-scale cycle is the mainstay and the domestic and international double cycles promote each other, the authors need to adopt a policy combination with the supply-side as the main and the demand-side as the supplement, and to work from both sides.

The purpose of this paper is to investigate the interactions among the key factors of supply chain (SC) in the Indian automotive industry. These key factors are helpful to measure supply chain performance (SCP) and to improve the firm’s effectiveness.

In this paper, an interpretive structural modeling with a fuzzy cross-impact matrix multiplication applied to classification-based approach is used to examine the interactions among the key factors of SCP measurement.

The authors have identified the most dominant key factors used for measuring the performance in automotive SC. The results exhibit that the order lead-time and order entry method are the most significant key factors. These key factors have high driving power to measure SCP whereas the post-transaction measure of customer service and customer query time are highly dependent on other factors. Such relationships among the key factors can help a firm’s top management to make essential judgments in order to solve the overall SC problems and provide a better approach to proactively deal with problems.

In this paper, the authors have explored the interactions among the key factors of the SCP in the Indian automotive industry.