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This study aims to investigate, for the first time in the literature, the stochastic properties of the US aggregate health-care price inflation rate series, using the data on health-care inflation rates for a panel of 17 major US urban areas for the period 1966-2006.

This goal is undertaken by applying the first- and second-generation panel unit root tests and the panel stationary test developed recently by Carrion-i-Silvestre et al. (2005) that allows for endogenously determined multiple structural breaks and is flexible enough to control for the presence of cross-sectional dependence.

The empirical findings indicate that after controlling for the presence of cross-sectional dependence, finite sample bias, and asymptotic normality, the US aggregate health-care price inflation rate series can be characterized as a non-stationary process and not as a regime-wise stationary innovation process.

The research findings apply to understanding of health-care sector price escalation in US urban areas. These findings have timely implications for the understanding of the data structure and, therefore, constructs of economic models of urban health-care price inflation rates. The results confirming the presence of a unit root indicating a high degree of inflationary persistence in the health sector suggests need for further studies on health-care inflation rate persistence using the alternative measures of persistence. This study’s conclusions do not apply to non-urban areas.

The mean and variance of US urban health-care inflation rate are not constant. Therefore, insurers and policy rate setters need good understanding of the interplay of the various factors driving the explosive health-care insurance rates over the large US metropolitan landscape. The study findings have implications for health-care insurance premium rate setting, health-care inflation econometric modeling and forecasting.

Payers (private and public employers) of health-care insurance rates in US urban areas should evaluate the value of benefits received in relation to the skyrocketing rise of health-care insurance premiums.

This is the first empirical research focusing on the shape of urban health-care inflation rates in the USA.

Customer reviews of mobile banking (m-banking) apps contain the most direct and first-hand accounts of customer experiences with m-banking. However, surprisingly little effort has been made to understand m-banking service quality using these reviews. Therefore, this study aims to discover m-banking service quality dimensions from customers' reviews of the m-banking apps through a text mining approach.

Reviews of m-banking apps of 24 banks operating in Pakistan were scraped from Google Play Store. Latent Dirichlet allocation (LDA) method was applied to discover the dimensions of m-banking service quality from 24,529 positive and 29,569 negative useable reviews.

Different dimensions of m-banking service quality are discussed in positive and negative reviews. Positive reviews focus on security, convenience, ease of use, continuous improvement, usefulness and app attributes, whereas negative reviews discuss system availability, responsiveness, faulty updates, login problems and reliability.

The results are based only on customer reviews in one country and generalization may not be possible. Moreover, due to the unavailability of demographic information about reviewers, the effect of demographic characteristics on users' perceptions of m-banking quality could not be determined.

The study provides managers with useful insights to improve the service experience of m-banking customers. The study also demonstrates how managers can employ text analytical techniques to assess and improve the quality of m-banking services.

In addition to enriching the understanding of m-banking quality based on direct and first-hand user experiences, the current study also provides initial evidence for the two-factor structure of m-banking service quality.

The purpose of this study is to find the thermo-hydraulic performances of compact heat exchangers (CHE’s), which are strongly depending upon the prediction of performance of various types of heat transfer surfaces such as offset strip fins, wavy fins, rectangular fins, triangular fins, triangular and rectangular perforated fins in terms of Colburn “j” and Fanning friction “f” factors.

Numerical methods play a major role for analysis of compact plate-fin heat exchangers, which are cost-effective and fast. This paper presents the on-going research and work carried out earlier for single-phase steady-state heat transfer and pressure drop analysis on CHE passages and fins. An analysis of a cross-flow plate-fin compact heat exchanger, accounting for the individual effects of two-dimensional longitudinal heat conduction through the exchanger wall, inlet fluid flow maldistribution and inlet temperature non-uniformity are carried out using a Finite Element Method (FEM).

The performance deterioration of high-efficiency cross-flow plate-fin compact heat exchangers have been reviewed with the combined effects of wall longitudinal heat conduction and inlet fluid flow/temperature non-uniformity using a dedicated FEM analysis. It is found that the performance deterioration is quite significant in some typical applications due to the effects of wall longitudinal heat conduction and inlet fluid flow non-uniformity on cross-flow plate-fin heat exchangers. A Computational Fluid Dynamics (CFD) program FLUENT has been used to predict the design data in terms of “j” and “f” factors for plate-fin heat exchanger fins. The suitable design data are generated using CFD analysis covering the laminar, transition and turbulent flow regimes for various types of fins.

The correlations for the friction factor “f” and Colburn factor “j” have been found to be good. The correlations can be used by the heat exchanger designers and can reduce the number of tests and modification of the prototype to a minimum for similar applications and types of fins.

The purpose of this paper is to evaluate the agility performance level of manufacturing supply chains using Taguchi loss functions (TLFs) and design of experiment (DoE).

The proposed methodology is used for capturing the various agility losses using appropriate TLFs and the aggregated agility loss is calculated at different situations using DoE. The aggregated agility loss is analysed for comparing manufacturing supply chain agility performance.

The proposed methodology was applied to three Indian auto component supply chains, i.e. X, Y and Z. In total, 27 experiments were carried out using DoE and obtained results show that agility performance level is the highest for X followed by Z, whereas agility performance level is the least for Y.

The proposed methodology is generic in nature and can be applied to a specific environment for comparing performance of different supply chains. The user has to identify the relevant agility enablers and capture the appropriate TLFs for the specific environment in which agility performance level has to be calculated and compared.

The proposed methodology provides an effective approach for evaluating agility performance. It can be used by the supply chain manger to assess the supply chain agility performance level of own company with its competitors. These comparisons will help the manufacturing company to find the areas where it should focus.

Many studies and researches related to implementation and evaluation of agile manufacturing are reported in the literature but very few studies are available for evaluating the supply chain agility performance. This study will definitely provide a guideline for measuring and comparing manufacturing supply chain agility performance in general and Indian automotive supply chain in specific.

The purpose of this paper is to clarify the confusion between flexibility and agility. The paper traces the evolution of agility and the evolution of flexibility over time, analyses their drivers and different elements, draws the boundaries between them and defines their relationship.

A systematic literature review of flexibility and agility was developed. Papers written between 1920 and 2017 were reviewed and analyzed using a structured review technique. The identified papers focus on flexibility and agility, relating both to manufacturing and the supply chain.

Agility is the natural evolution of flexibility. Until the 1990s, the term “flexibility” was used to refer to agility, but, because of market changes, competitiveness and the need for speed, the term “agility” was coined. While flexibility is considered as an operational ability, agility is a strategic ability that enables a firm to establish a strategic long-term vision. In fact, flexibility is an agility capability, among other capabilities such as responsiveness or speed. There are also several types of flexibility that are used as agility sub-capabilities, or as agility enablers, which further confirms the idea that flexibility is a part of agility.

This research is a systematic review of the existing literature on the concepts of flexibility and agility. Although it is theoretical, it could provide a set of hypotheses that would enable an empirical study to be conducted into how firms from different industries perceive flexibility and agility and how they implement each of them.

Flexibility and agility are two distinct characteristics that enable a firm to gain a competitive advantage by responding quickly and effectively to changing customer demand. However, there is confusion between these two concepts in the academic and professional literature, with both terms being used to refer to the same idea. Our literature review aims to draw the boundaries between flexibility and agility by analyzing the evolution of the two concepts and detailing their respective drivers and elements, in order to bring more clarity to the nature of the relationship between flexibility and agility.