Search results

This paper recasts the land development problems of Williams (1991) and Quigg (1993) by explicitly dealing with the effects of scale elasticity of unit rental and unit construction cost in a real estate project. Two different diseconomies of scale constraints are imposed on the rental and cost variables. We assume a concave function for the rental variable with respect to the scale of development. Whereas, on the cost side, the diseconomies of scale effect of the variable component of the construction cost is incorporated via a elasticity of scale factor that is larger than unity. The comparative statics simulated positive relationships between the premium that keeps the option of waiting to develop alive and the volatilities of the unit rental and unit construction cost. It was also found that the cost elasticity of scale and the financing cost are factors that increase the premium of the waiting option, whereas, the rental yield factor reduces the incentive of waiting. A high rental yield tends to expedite a development project because the opportunity cost of not developing the land is high. In the case analysis involving a vacant land of 8,000 square meters at Spitafield, East London, a unit rental of £267.2 per square meter (psm) is obtained, which would breakeven a cash flows of the project when the traditional “invest now or never” assumption is made. Compared with the optimal unit rental of £677.0 psm estimated by the real option model, the traditional DCF results tend to accept the feasibility of the real estate project too early and at too low a cut‐off rental.

Establishing the validity and measurement equivalence of core marketing concepts in the emerging market economies of Africa is a key step in assessing the transferability of modern marketing theory and managerial practice to these countries. However, measurement equivalence issues are rarely addressed in studies of marketing practices in Africa. Accordingly, this study examines the equivalence of core marketing concepts based on interviews of 459 marketing managers from Kenya, Nigeria, Japan and the USA. The results show that optimal scaling analysis of the managers’ evaluations provide more valid and meaningful assessment than that of the raw data. The managers’ evaluations of the concepts revealed amazingly similar or prototypical perceptions of marketing’s core concepts and its applicability in their organizations, despite the profound country environmental differences. It appears that the concepts fall into two cross‐national categories of applicability that permeate the industrialized and developing country categorization. Managerial and research implications are discussed.

The purpose of this study is to evaluate the category function of the sport fandom questionnaire (SFQ), determine the optimal categorization of the SFQ and calibrate the measurement qualities of the newly modified rating scale option using Rasch analysis.

This paper relies on the Rasch analysis to validate the SFQ. A series of studies are performed based on analysis procedures for the responses from 244 (study 1) and 477 (study 2) participants.

The results revealed that the original SFQ consisting of the eight-category rating scale is flagged due to irregular observation distribution and disordering of thresholds, whereas both six-category and seven-category rating scales meet the guidelines for the optimal categorization. However, only the seven-category rating scale showed desirable model-data fit indices. Furthermore, the results of the Rasch calibration model showed that all items of the SFQ have large variability, and a person's ability level varied moderately along the continuum.

Unlike previous studies, examining the psychometric properties of the SFQ, the current study provides information about the optimal categorization and presents a novel reconstruction category in measuring individuals' sport fandom level. In measuring the level of sport fandom, the authors suggest the use of a seven-category rating scale that the current study found to exhibit reliability and construct validity.

The Analytical Hierarchy Process (AHP), a multicriteria decision support system that has been successfully applied to numerous decision-making situations, has been applied to patient assessment. The AHP was used with Timeslips™, a group storytelling program that encourages creative expression among dementia patients, to determine the optimal scale for pre and post assessment among the nine most common agitation and anxiety scales. The AHP used the six criteria identified by qualitative assessment of the nine scales: (1) validity/reliability, (2) observation period, (3) training required, (4) time to administer, (5) most appropriate administrator, and (6) accessibility/cost. The AHP indicated that the Overt Agitation & Anxiety Scale was optimal for use with Timeslips; the process and results are discussed.

Data envelopment analysis (DEA) and window analysis are used to follow the changes in Australian trading banks' pure technical efficiency, scale efficiency, and the nature of returns to scale. The main findings indicate declining average efficiency scores until 1991, followed by a steady rise thereafter. Pure technical inefficiency emerges as a greater source of inefficiency than scale inefficiency. Overall, regional banks exhibit increasing returns to scale and major trading banks exhibit decreasing returns to scale. Also worthy of note is the mixed size of banks operating at optimal returns to scale.

Data envelopment analysis (DEA) is a significant method for measuring the relative efficiency of decision making units (DMUs) that use the least inputs, produce the most desirable outputs and emit the least undesirable outputs in order to maximize their profits. In DEA, detecting an optimal scale size (OSS) is also vital and could be more applicable in economic activities when there are integer and undesirable measures. The purpose of this research is to measure average-profit efficiency (APE) and OSSs with integer data and undesirable outputs.

This study presents an alternative concept of APE using the concepts of most productive scale size (MPSS), profit efficiency and scales, containing desirable and undesirable outputs along with integer and non-integer measures. In fact, the OSS minimizes APE as the optimal scale, which is the ratio of the profit efficiency to the radial average output. Considering the prices of the inputs and desirable outputs, as well as the lack of any specific weight for the undesirable outputs, a two-step model for the numerical calculation of OSS is presented. In addition, the proposed approach is applied to a real data set of Iranian gas companies while there are integer measures and undesirable outputs.

The results show the introduced approach is beneficial to estimate OSSs from the aspect of maximizing profits of firms with undesirable outputs and integer values.

Estimating OSSs is the significant issue for managers, but its investigation in the presence of integer measures and undesirable outputs is presently under-considered.

The purpose of this paper is to analyse the performance of the Indian non-life (general) insurance sector in terms of efficiency, productivity and returns-to-scale economies. In addition to this, it identifies the determinants of efficiency.

This study employs a two-stage data envelopment analysis (DEA) bootstrap approach to estimate the level and determinants of efficiency. In the first stage, the DEA bootstrap approach is employed to estimate bias-corrected efficiency scores. In the second stage, the truncated bootstrapped regression is used to identify the effect of firm-level characteristics on the efficiency of insurers. Moreover, the bootstrapped Malmquist index is used to examine the productivity growth over the observation period 2005–2016.

The bootstrapped DEA results show that the Indian non-life insurance sector is moderately technical, scale, cost and allocative efficient, and there is a large opportunity for improvement. Moreover, the results reveal that the public insurers are more cost efficient than the private insurers. It is also evident that all the insurers irrespective of size and ownership type are operating under increasing returns to scale. Malmquist index results divulge an improvement in productivity of insurers, which is attributable to the employment of the best available technology. Bootstrapped DEA and bootstrapped Malmquist index results also show that the global financial crisis of 2008 has not severely affected the efficiency and productivity of the Indian non-life insurance sector. The truncated regression results spell that size and reinsurance have a statistically significant negative relationship with efficiency. It also shows a statistically significant positive age–efficiency relationship.

The results hold practical implications for the regulators, policy makers, practitioners and decision makers of the Indian non-life insurance companies.

This study is the first of its kind that comprehensively investigates different types of robust efficiency measures, determinants of efficiency, productivity growth and returns-to-scale economies in the Indian non-life insurance market for an extended time period.

The purpose of this paper is to analyse the performance of the Indian non-life (general) insurance sector in terms of total factor productivity (TFP) over the period 2005–2016.

This study utilises Färe‒Primont index (FPI) to access the change in TFP and its components: technical change, technical efficiency and mix and scale efficiency over the observation period. Moreover, it employs the Mann–Whitney U-test to scrutinise the difference between the public and the private insurers in terms of growth in productivity.

The results reveal that the insurance sector possesses a very low level of TFP. Also, the results divulge an improvement of 11.98 per cent in TFP of the insurance sector at an annual average rate of 12.41 per cent over the observation period. The growth in productivity is mainly attributable to the improvement of 10.81 per cent in the scale‒mix efficiency. The progress in scale‒mix efficiency is mainly the result of improvements in residual scale and residual mix efficiency. The results also show that the privately owned insurers have experienced a high productivity growth rate than the state-owned insurers.

The results hold practical implications for the regulators, policymakers and decision makers of the Indian non-life insurance companies.

This study is the first of its kind to use FPI, which satisfies all economically relevant axioms and tests defined by the index number theory to comprehensively access the change in TFP of the Indian non-life insurance sector.