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The relationship between multinationality and firm performance is a central issue in the international marketing and business literatures. Predominantly, this body of research has tried to identify a single, generalized pattern for this relationship. However, despite the vast number of studies, results have been characterized as mixed or inconsistent. In this study, we take a fresh look at this relationship.

We focus on a key inducement to expand firm multinationality – the search for a more efficient way to exploit firm resources, and also on a specific operationalization of multinationality – firm geographic scope. We use a formal analytical model analyzing the trade-off between benefits and costs arising from expanding firm geographic scope and emphasizing the role of lumpy costs emanating from resource indivisibility.

The relationship between geographic scope and performance cannot be confined to a single pattern, but instead, may have any one of a set of patterns: negatively monotonic shape, inverted U-shape, S-shape, M-shape or, multiple-wave inverted U-shape.

The current study offers managers some guidelines to identify which of the above patterns fits their firm's specific case, and to identify the optimal level of geographic scope for their firm.

We conclude that the search for a single, generalized pattern for multinationality-performance is largely futile, whereas the focus on specific inducements and operationalizations for multinationality allows us to explain when and why specific patterns are more likely to occur.

This chapter demonstrates how the ‘golden rule’ can be applied by operators of flexible transport services to improve investment and pricing decisions.

The chapter explains why an appropriate decision making framework is particularly important for operators of flexible transport services and compares the traditional economic framework of fixed versus variable costs to the decision-oriented approach that analyses the activities of a firm in terms of costs that are avoidable (i.e. specific to a particular activity) and costs that are shared amongst a number of activities. The chapter introduces the ‘golden rule’ of decision making and discusses issues in implementing the rule.

An economic framework for decision making is particularly important for smaller scale transport operations (such as flexible transport services) because ‘lumpy’ investment costs are more significant than for larger operators. The traditional economic approach divides costs into fixed costs and those which vary by patronage. A better framework for decision making divides costs into those which are specific to a particular activity and, therefore, avoidable if that activity ceases, and those costs which are common to more than one activity.

Using this framework allows operators to apply the ‘golden rule’ in pricing their services so that the avoidable costs of each activity are recovered and the enterprise covers its shared costs overall.

This chapter will be useful to operators of flexible transport services who are new to the industry or are reacting to changes in the funding environment.

In recent decades there has been much interest and activity in the application of mathematical ideas for controlling inventory. However most of this has been related to the control of stock products whose demand is smooth and continuous. When demand is lumpy these methods are inefficient in their attempts to minimise thé operating cost. A simple regression model is developed for computing optimal (s, S) policies for items with lumpy demand patterns. Continuous review of inventory level is assumed and the lead time demand is approximated by the stuttering Poisson distribution. A grid of 864 known optimal policies has been used to provide the data for the calibration of the regression models. Numerical models are used to illustrate this approach. Extensive computational results show that this model provides excellent performance in estimating the optimal values of the control parameters s and S for wide ranges of demand and cost parameters.

Although some recent articles have extended the traditional economic order quantity models to JIT purchasing, their value is limited by the simplistic nature of the underlying assumptions. Implementation of JIT procurement is a lengthy and complex process and it is important to recognize the interrelationships between the investments in the different subsystems of the procurement system to suit JIT and the resultant cost and lead time structures. It is also important o consider the variability in demand and lead time. Presents an inventory‐theoretical model that takes these considerations into account and illustrates its application with a numerical example. This model facilitates the choice of an optimal combination of the investment and the shipment lot size to minimize the total annual cost in each period as a firm progressively adopts JIT procurement.

Past research in examining the performance of alternative lot‐sizing rules has focused on the total cost of inventory carrying cost and set‐up cost. Although this cost‐related performance measure is significant for evaluating the overall efficiency of production systems, there are other variations such as frequent rescheduling, generally referred to as system nervousness, occurring that would affect the production scheduling and subsequently the system performance. Expands the performance criteria to re‐evaluate the effectiveness of using several commonly tested lot‐sizing rules in a multi‐level MRP system under stochastic operating environments by means of a simulation study. Results indicate that the Silver‐Meal algorithm seem to perform very well under most operating environments tested. Also, the operating environments play a significant role in the relative performance of lot‐sizing rules tested.

The downturn in the residential housing market in Northern Ireland (NI) has been the most pronounced of any UK region, with house prices contracting circa 40 per cent between 2007Q3 and 2009Q4. The downturn at first glance appears to have increased the “ability to afford” however this is nonetheless a “false dawn”. Significant deposit levels coupled with a more prudent lending culture has ensured that housing affordability remains a primary policy concern. The purpose of this paper is to empirically analyse the interrelationships between mortgage liquidity and housing affordability in NI during the boom‐bust cycle in the residential property market.

The paper analyses mortgage‐lending statistics for NI in the period 1993‐2009, using time series panel data. House price data are drawn from the University of Ulster House Price Index over the same time series. To facilitate analytical interpretation and outcome analysis, quantitative evaluation is applied within a first‐time buyer (FTB) affordability framework.

This study finds that the relationship between mortgage finance and affordability has been driven by deregulation of the mortgage market contributing to the rise in house prices and affordability pressures during the market up cycle. More recently, ongoing liquidity constraints within the financial sector are impairing recovery in the residential property market culminating in heightened concerns of both purchase and “deposit gap” affordability. The key findings suggest that the new significant capital requirement needed to access the housing market will inevitably prolong affordability pressures for the foreseeable future.

This paper contributes to affordability debate in two ways. First, it examines the effect of both liberalised and contracted patterns of mortgage finance on affordability and argues that conventional approaches appear to present a “false dawn” for FTBs in NI. Second, the paper demonstrates that affordability post‐financial crisis has shifted in genre towards a purchase and deposit gap (lag time) issue.

With significant changes in the aviation industry, various airport–airline arrangements have been formed to achieve alternative objectives. However, no consensus has been reached on such arrangements’ economic effects and the associated optimal public policy. This chapter aims to provide an interpretive review of the common types of airport–airline arrangements, the different modeling approaches used and key conclusions reached by recent studies. Our review suggests that airport–airline arrangements can take diverse forms and have been widely used in the industry. They may allow the airport and its airlines to internalize demand externality, increase traffic volume, reduce airport investment risks and costs, promote capacity investment, enhance service quality, or simply are a response to the competition from other airport–airline chains. On the other hand, such vertical arrangements, especially for those exclusively between airports and selected airlines, could lead to collusive outcomes at the expenses of non-participating organizations. The effects of such arrangements are also significantly influenced by the contract type, market structure and bargaining power between the airport and airline sectors. While case by case investigations are often needed for important economic decisions, we recommend policy-makers to promote competition in the airline and airport segments whenever possible, and demand more transparency or regulatory reporting of such arrangements. Policy debates and economic studies should be carried out first, before intrusive regulations are introduced.