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A method has been developed for the solution of inverse heat diffusion problems to find the initial condition, boundary condition, and the source and sink function in the heat diffusion equation. The method has been used in the development of a source‐and‐sink method to find the boundary conditions in inverse Stefan problems. Green's functions have been used in the solution, and the problems are solved by using two approaches: a series solution approach, and a time incremental approach. Both can be used to find the boundary conditions without reliance on the flux information to be supplied at both sides of the interface. The methods are efficient in that they require less equations to be solved for the conditions. The numerical results have shown to be accurate, convergent, and stable. Most of all, the results do not degrade with time as in other time marching schemes reported in the literature. Algorithms can also be easily developed for the solution of the conditions.

A method has been developed for conjugate heat transfer analysis of fluid flow inside parallel channels formed by a phase change material (PCM) separated from the fluid by a wall. The phase change in the PCM is two dimensional and a hybrid analysis consisting of an analytical solution in one direction and a finite‐difference method in another direction is used to solve for the temperature in the PCM. The heat transfer fluid (HTF) inlet temperature is given and the heat transfer between the HTF and the PCM is treated as a conjugate problem that requires no iterations to obtain a solution. The numerical results are found to be stable, convergent, and accurate. Application of the method to the solution of heat extraction from a phase‐change energy storage unit is given in detail and the numerical results are shown to be accurate, based on an energy conservation analysis, to within 3%.

The rapid increase in analytics is playing an essential role in enlarging various practices related to the health sector. Big Data Analytics (BDA) provides multiple tools to store, maintain, and analyze large sets of data provided by different systems of health. It is essential to manage and analyze these data to get meaningful information. Pharmaceutical companies are accumulating their data in the medical databases, whereas the payers are digitalizing the records of patients. Biomedical research generates a significant amount of data. There has been a continuous improvement in the health sector for past decades. They have become more advanced by recording the patient’s data on the Internet of Things devices, Electronic Health Records efficiently. BD is undoubtedly going to enhance the productivity and performance of organizations in various fields. Still, there are several challenges associated with BD, such as storing, capturing, and analyzing data, and their subsequent application to a practical health sector.

Many bike rental organizations permit customers to pick-up bikes from one bike station and return them at a different one. However, this service may result in bike imbalance, as bikes may accumulate in stations with low demand. To overcome the imbalance problem, this paper aims to develop a decision model to minimize the total costs of unmet demand and empty bike transport by determining bike fleet size, deployments and the vehicle routing schedule for bike transports.

This paper developed a constrained mixed-integer programming model to deal with this bike imbalance problem. The proposed model belongs to the non-deterministic polynomial-time (NP)-hard problem. This paper developed a two-phase heuristic approach to solve the model. In Phase 1, the approach determines fleet size, deployment level and the number of satisfied demands. In Phase 2, the approach determines the routing schedule for bike transfers.

Computational results show the following results that the proposed approach performs better than General Algebraic Modeling System (GAMS) in terms of solution quality, regardless of problem size. The objective values and the fleet size of rental bikes allocated increase as the number of rental stations increases. The cost of transportation is not directly proportional to the number of bike stations.

The authors provide an integrated model to simultaneously deal with the problems of fleet sizing, empty-resource repositioning and vehicle routing for bike transfer in multiple-station systems, and they also present an algorithm that can be applied to large-scale problems which cannot be solved by the well-known commercial software, GAMS/CPLEX.

The purpose of this paper is to investigate the effect of the determinants of corporate effective tax rates (ETR) of listed companies in euro area.

With a large and recent panel of 2,870 listed companies for the period 2005–2016, the authors use the generalized moments method (GMM) to estimate global models for three groups of countries and specific models for six selected countries: Germany, Spain, France, Italy, Belgium and Greece.

The results confirm that ETR have different determinants depending on the countries analyzed. There is a significantly positive relationship with leverage and negative with size and financial profitability. However, economic profitability shows a statistically positive effect in the new members, but negative effect on old ones. In the individual analysis, Germany and Spain maintain this negative association with return on assets (ROA), but Belgium and Greece show a positive effect. The effect of the economic cycle shows statistically relevant, negatively in Germany but positively in Belgium and Greece.

This paper makes a novel contribution to the current debate on the need for harmonization of corporate income tax in the European Union (EU). For the first time, the group of countries whose common currency is the euro is considered with a great level of detail. In addition, the impact derived from the enlargement of the euro area and the individual analysis of the main countries is included. The European authorities must take into account the specific differences found in the ETR determinants because it hinders to take measures that limit tax competition.

El propósito de este artículo es investigar el efecto de los determinantes del tipo impositivo efectivo (TIE) del impuesto de sociedades de las empresas que cotizan en la zona del euro.

Utilizando un panel de 2,870 compañías cotizadas en el período 2005–2016, los autores utilizan el Método de Momentos Generalizados (GMM) para estimar modelos globales para tres grupos de países y modelos específicos para los seis países seleccionados: Alemania, España, Francia, Italia, Bélgica y Grecia.

Los resultados confirman que el TIE tiene diferentes determinantes en función de los países analizados. Entre antiguos y nuevos miembros se evidencia una relación significativamente positiva con el apalancamiento y negativa con el tamaño y la rentabilidad financiera. Sin embargo, la rentabilidad económica muestra una relación estadísticamente positiva en los nuevos, pero negativa en los antiguos. En el análisis individual, Alemania y España mantienen esta asociación negativa con el ROA, pero Bélgica y Grecia evidencian un efecto positivo. El efecto del ciclo económico sí resulta estadísticamente relevante, de forma negativa en Alemania, pero positiva en Bélgica y Grecia.

Este artículo hace una novedosa contribución al debate actual sobre la necesidad de armonizar del impuesto de sociedades en la Unión Europea. Por primera vez, se considera el grupo de países cuya moneda común es el euro con gran nivel de detalle, así como el impacto de su ampliación y la comparativa individual entre sus principales países. Las autoridades europeas deberían tener en cuenta las específicas diferencias encontradas en los determinantes del ETR, tanto entre antiguos y nuevos miembros como por países, porque dificultan la adopción de medidas de armonización que limiten la competencia fiscal entre países comunes.

In order to reduce avoidably lengthy duration required to test highly reliable products under usage stress, accelerated life test sampling plans (ALTSPs) are employed. This paper aims to build a decision model for obtaining optimal sampling plan under accelerated life test setting using Type-I hybrid censoring scheme for products covered under warranty.

The primary decision model proposed in this paper determines ALTSP by minimizing the relevant costs involved. To arrive at the decision model, the Fisher information matrix for Type-I hybrid censoring scheme under accelerated life test setting is derived. The optimal solution is attained by utilizing appropriate techniques following a nonlinear constrained optimization approach. As a special case, ALTSP for Type-I censoring is obtained using the same approach. ALTSP under Type-I hybrid censoring using the variance minimization approach is also derived.

On comparing the optimal results obtained using the above mentioned approaches, it is found that the cost minimization approach does better in reducing the total cost incurred. Results also show that the proposed ALTSP model under cost function setting has considerably lower expected testing time. Interesting findings from the sensitivity analysis conducted using a newly introduced failure dataset pertaining to locomotive controls are highlighted.

The research introduces a model to design optimum ALTSP for Type-I hybrid censoring scheme. The practical viability of the model makes it valuable for real-life situations. The practical application of the proposed model is exemplified using a real-life case.

Stimulated by trends in group purchasing and online social communities, consumers are changing their shopping behavior and increasingly turning to websites for their shopping needs. The purpose of this paper is to investigate how website quality influences shopping websites to create value for the customer and promote loyalty among customers, as well as moderating effects of online shopping experience.

This study collected data from 275 respondents for testing against the proposed research model by means of the partial least squares (PLS) path modeling. ADANCO software was used to assess the reliability and validity of the measurement model, conduct an analysis of the goodness of model fit for the overall model, and test the hypotheses through structural modeling.

Empirical results demonstrate that system quality and electronic service quality (e-service quality) have a significant positive effect on the perceived value of consumer/seller relationship; the perceived value of the consumer/seller relationship has a significant positive effect on online loyalty; online shopping experience does not exert a moderating effect on the relationship between website quality and the perceived value of consumer/seller relationship.

This study applied the PLS path modeling approach using ADANCO variance-based structural equation modeling software to verify that website quality plays an important role in distinguishing a brand from other brands in e-tailing, making it an essential factor of a shopping website’s business success. This study further verified that the amount of previous online shopping experience a consumer has does not interfere with the positive influence that website quality exerts on the perceived value of the consumer/seller relationship. The above indicates that it is imperative for website managers to adopt online shopping experience of consumers as a market segmentation variable so as to enhance website quality, increase the perceived value of consumer-seller relationships, and win consumer loyalty.

Nowadays companies are constantly changing their retail settings and strategies to keep up with technological developments and consumer needs. Digital transformation enabled one’s shopping experience to be more efficient in terms of money, time, physical effort and other elements that determine the price a consumer has to pay. Channels of communication and distribution have evolved, increased in number and also became integrated. Mobile devices, mobile applications and location services help consumers in their shopping journey. These developments have led us to a new concept called omni-channel management. In theory, the omni-channel refers to a single and unified channel experience with multiple touchpoints, which include physical stores, online stores and direct marketing; mass communication channels (television, radio, print media, C2C, etc.), online channels (social media, search engines, comparison sites, e-mail, display etc.) and mobile channels (SMS, branded apps, etc.). Some examples of omni-channel practices are click-reserve, click-collect, tablets as in-store sales tools, in-store product order through mobile apps, etc.

In this chapter, the latest trends in marketing channels are discussed with enabling digital technologies and relevant success factors. Challenges and opportunities in implementing omni-channel strategies and several omni-channel initiatives from Turkey are reported.

A research was employed to present consumers’ preferences of touchpoints/channels for search, payment and delivery, and to find out the drivers that lead consumers to use more than one channel simultaneously and/or interchangeably in a buying process. The results will guide the readers to understand consumer behaviour in the new omni-channel world.

Export manufacturing firms from emerging markets can better meet customer needs by providing customization, which leads to competitive advantages. Although both practice and academic research have deeply discussed customization, the question of whether customization promotes export manufacturing firms' product innovation in the global B2B market is largely unexplored. The purpose of this paper is to address this issue.

This paper collects survey data from 2,248 export manufacturing firms in China and uses hierarchical moderated regression to explore the relationship between customization and product innovation in the global B2B market and their boundary conditions.

This research shows that customization positively affects export manufacturing firms' product innovation in the context of the global B2B market, and it shows that internal governance structure (contract governance and relationship governance) and external governance structure (legal enforceability) can be used as boundary conditions that affect the relationship. Specifically, contract governance has an inverted U-shaped moderating effect on the relationship between customization and product innovation; moreover, relationship governance and legal enforceability can strengthen the positive relationship between customization and product innovation.

The study explores the relationship between customization and product innovation in the global B2B market and examines the moderating effect of internal and external governance structures. In addition, the study enriches the research related to customization and product innovation in the context of the global B2B market and provides essential practical insight into the survival of export manufacturing firms from emerging markets.