New ways of interacting with culture consumers through cultural services marketing using Big Data and IoT

This paper presents the definition of cultural marketing services phenomena, trying to identify new ways to interact and gain insight in consumer preference and behavior. The existence of Big Data and Internet of Things can be used in the Cultural Services sector. Traditional marketing and digital marketing can be reunited with the help of Big Data trends and analytics to better connect with target audience. Big Data can be used to analyze and discover new patterns in social trends and uncover customer preference. There are digital ways in which now consumers interact with their favorite cultural service and these are mostly, by internet. This new level of interaction live with your favorite cultural service, band or artist, even with other services like museums or conferences, where a human voice exists, can make the difference between returning or not to a certain service. Customizing the experience for each customer gives way to improving the overall marketing mix and improve profits. Big Data can help at improving this experience and create a better hypothesis for future strategies used in new cultural events. The main objective of marketing cultural services is to offer the client a unique selling proposition that can’t be refused. Using the internet, they leave a digital footprint with every action they make in regard with a certain services: they engage via social networks or check in via GPS. These are just a few examples of raw data that can be collected and used to exemplify future possibilities and predict where people will be in relation with a certain cultural call to action. This information, with consumer behavior studies, motivations, drives and other characteristics (age, sex, income, social position) can determine the best marketing approach for a certain event or communication in order to achieve maximum return on investment

Creative and cultural industries in Europe – case study of the performing arts in Romania

Culture is one of the most important aspects of being human alongside education. A very interesting way of approaching the issue of culture is understanding the importance of the art in everyday life. Alan Peacock, one the first pioneers of the term cultural economy, was a man of the arts who understood the importance of culture, not only in life, but in economy. Many writers in the 1960s identified some opportunities in engaging in the cultural and arts industries. As we know, cultural goods have an economic value and an artistic value. The evaluation of artistic goods or products is made only after it is consumed by clients or customers. The world of cultural services is large and forgiving with non-professionals. The use of cultural policies in today’s European Union, United States of America and Asia is very important because of the positive spillover it causes. Creating cultural policies and dedicating funds specifically for this started in the 1980s with the implication of UNESCO. Cultural policies not only help preserve cultural sites and heritage, but offers a broader strategy that envelops both cultural goods and cultural services. The cultural marketing concept refers to the art of using marketing tactics and strategies in order to promote and develop the cultural and artistic industries or sectors. The same instruments are used but the way in which they are used is very different. The performing arts sector is ever changing and it needs a new marketing mix approach to connect to new audiences. Artists need to work closely with business and management professionals in order to have the best representation off stage

Technological Change and Catching-Up in the Indian Banking Sector: A Time-Dependent Nonparametric Frontier Approach

© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.This paper investigates whether there has been any improvement in efficiency convergence of banks in India during the post-reform period considering bank ownership structures, using a balanced panel for 73 banks over the time period 1996–2014. Utilizing nonparametric frontier estimators, we compute time-dependent bank efficiency scores, which allow us to examine the dynamics of technological frontier and catch-up levels of Indian banks, and to explore the convergence patterns in the estimated efficiency levels. Our results signify that the state-owned banks, which dominate the banking activity in India, establish themselves as the best performers, ahead of the private, foreign and cooperative banks during post-2005. Even during the recent global financial crisis period, we find that bank efficiency levels increased, except for foreign banks which have had the greatest adverse impact. The convergence results show that heterogeneity is present in bank efficiency convergence, which points to the presence of club formation suggesting that Indian banks’ efficiency convergence is partly driven by the ownership structure.Peer reviewedFinal Published versio

Explaining inefficiency in nonparametric production models: the state of the art

The performance of economic producers is often affected by external or environmental factors that, unlike the inputs and the outputs, are not under the control of the Decision Making Units (DMUs). These factors can be included in the model as exogenous variables and can help to explain the efficiency differentials, as well as improve the managerial policy of the evaluated units. A fully nonparametric methodology, which includes external variables in the frontier model and defines conditional DEA and FDH efficiency scores, is now available for investigating the impact of external-environmental factors on the performance. In this paper, we offer a state-of-the-art review of the literature, which has been proposed to include environmental variables in nonparametric and robust (to outliers) frontier models and to analyse and interpret the conditional efficiency scores, capturing their impact on the attainable set and/or on the distribution of the inefficiency scores. This paper develops and complements the approach of Bădin et al. (2012) by suggesting a procedure that allows us to make local inference and provide confidence intervals for the impact of the external factors on the process. We advocate for the nonparametric conditional methodology, which avoids the restrictive “separability” assumption required by the two-stage approaches in order to provide meaningful results. An illustration with real data on mutual funds shows the usefulness of the proposed approach

Comparing the Efficiency of Hospitals in Italy and Germany: Nonparametric Conditional Approach Based on Partial Frontier

Traditional nonparametric frontier techniques to measure hospital efficiency have been criticized for their deterministic nature and the inability to incorporate external factors into the analysis. Moreover, efficiency estimates represent a relative measure meaning that the implications from a hospital efficiency analysis based on a single-country dataset are limited by the availability of suitable benchmarks. Our first objective is to demonstrate the application of advanced nonparametric methods that overcome the limitations of the traditional nonparametric frontier techniques. Our second objective is to provide guidance on how an international comparison of hospital efficiency can be conducted using the example of two countries: Italy and Germany. We rely on a partial frontier of order-m to obtain efficiency estimates robust to outliers and extreme values. We use the conditional approach to incorporate hospital and regional characteristics into the estimation of efficiency. The obtained conditional efficiency estimates may deviate from the traditional unconditional efficiency estimates, which do not account for the potential influence of operational environment on the production possibilities. We nonparametrically regress the ratios of conditional to unconditional efficiency estimates to examine the relation of hospital and regional characteristics with the efficiency performance. We show that the two countries can be compared against a common frontier when the challenges of international data compatibility are successfully overcome. The results indicate that there are significant differences in the production possibilities of Italian and German hospitals. Moreover, hospital characteristics, particularly bed-size category, ownership status, and specialization, are significantly related to differences in efficiency performance across the analyzed hospitals

Using nonparametric conditional approach to integrate quality into efficiency analysis: empirical evidence from cardiology departments

Health care providers are under pressure to improve both efficiency and quality. The two objectives are not always mutually consistent, because achieving higher levels of quality may require additional resources. The aim of this study is to demonstrate how the nonparametric conditional approach can be used to integrate quality into the analysis of efficiency and to investigate the mechanisms through which quality enters the production process. Additionally, we explain how the conditional approach relates to other nonparametric methods that allow integrating quality into efficiency analysis and provide guidance on the selection of an appropriate methodology. We use data from 178 departments of interventional cardiology and consider three different measures of quality: patient satisfaction, standardized mortality ratio, and patient radiation exposure. Our results refute the existence of a clear trade-off between efficiency and quality. In fact, the impact of quality on the production process differs according to the utilized quality measure. Patient satisfaction does not affect the attainable frontier but does have an inverted U-shaped effect on the distribution of inefficiencies; mortality ratio negatively impacts the attainable frontier when the observed mortality more than doubles the predicted mortality; and patient radiation exposure is not associated with the production process