Revenue efficiency evaluation of life insurance companies in India: identification of leaders and laggards

PurposeThe purpose of this article is to evaluate revenue efficiency performance of life insurance companies in India. The study also compares if private or public insurance sector is more “revenue efficient”. Furthermore, the study determines the nature of return to scale (RTS) and identifies the leaders and laggards amongst insurance companies operating in India.Design/methodology/approachRevenue efficiency is calculated by employing data envelopment analysis – a non-parametric approach, on a data set of 24 insurance companies over the period 2013–2014 to 2017–2018.FindingsThe empirical results suggest that life insurance companies in India could generate only 34.4% of revenue, which is very less than what these are expected to generate from the same inputs. Majority of life insurance companies operating in India are operating at decreasing return to scale (DRS). There is a reduction in leaders and the highest proportion of companies is falling in the category of laggards.Originality/valueAs per the best knowledge of researchers, no empirical work has been carried out with respect to measuring the revenue efficiency of Indian insurance companies. The current study appropriately fills the gap by not only calculating the revenue efficiency scores of insurance companies in India but also provides insights into the causes of revenue inefficiencies. It also gives implications for efficient and effective management of insurance companies.

Platform Revenue Strategy Selection Considering Consumer Group Data Privacy Regulation

In the era of big data, consumer group privacy has become an important source of revenue for the digital platform. Considering the situation that the platform collects consumer group data privacy to generate business revenue, we explore how the service matching level and commission rate affect the platform revenue, social welfare, and seller benefits. Based on the theory of group privacy, the three-party equilibrium evolution is solved by constructing a sequential game model including platform, seller, and consumer alliance. It is found that when the service matching level of the platform is greater than the threshold value, there are two main situations: on the one hand, if using the data privacy of a consumer group is subject to market regulation, the platform will set a high commission rate and service matching level in order to maximize profit. However, social welfare and seller’s business benefit both reach a minimum in this case, and the three-party game cannot attain equilibrium. On the other hand, when the market governor relaxes the platform’s regulation on the use of consumer group privacy data and data revenue efficiency is high enough, the platform can maximize the revenue by increasing the service matching level and reducing the commission rate. The optimal commission rate depends on the data revenue efficiency of the platform. Moreover, when the platform sets the highest commission rate and the service matching level is at a medium level, a stable partial equilibrium among the three-party will be achieved. These conclusions can give some insights into platform’s business model choice decision.

Cost Efficiency Vis-à-Vis Revenue Efficiency Analysis of Indian Scheduled Commercial Banks in a Dynamic Environment

The paper endeavours to analyze Cost Efficiency vis-à-visRevenue Efficiency of Scheduled Commercial Banks (SCBs) as well as across ownership in India. Data Envelopment Analysis (DEA) has been employed to calculate the efficiency scores of SCBs over five points of time i.e. 2000-01, 2004-05, 2008- 09, 2012-13 and 2016-17. The differences in the efficiency scores are examined by applying Analysis of Variance (ANOVA). The results of Cost and Revenue Efficiency of Indian Scheduled Commercial Banks highlight that the highest level of inefficiency subsist on the cost side as Scheduled Commercial Banks have higher Revenue Efficiency scores in comparison to Cost Efficiency scores. Cost Efficiency across ownership shows that Public Sector Banks have higher Cost Efficiency in 2000-01. Private Sector Banks are cost efficient in 2004-05 while Foreign Sector Banks show higher Cost Efficiency scores in 2008-09, 2012-13 and 2016-17. Revenue Efficiency scores shows that Public Sector Banks have higher scores as compared to Private and Foreign Sector Banks in the 2000-01 and 2004-05. Foreign Sector Banks are revenue efficient in 2008-09 and 2016-17 with Private Sector Banks taking the lead in 2012-13. The results of ANOVA reveal that there exists a statistically significant difference in Cost Efficiency and Revenue Efficiency among banks in different sectors over different points of time.

A meta-crisis banking efficiency study in the MENA region

Purpose The purpose of this paper is to comparatively examine the cost and the overlooked revenue efficiency of Islamic and commercial banks in the aftermath of the crisis, operating in nine MENA-based countries during the 2010-2017 financial period, where the established empirical work is relatively limited. The authors also update the research where they use recent data sets and they provide for a targeted, structured literature review pre- and post-crisis in the Gulf region. Design/methodology/approach The authors examine cost and revenue efficiency of 25 major Islamic banks (IBs) and 25 major conventional banks (CBs). They conduct tests on the determinants of such variables. In the first stage of the analysis, they measure efficiency by using the data envelopment analysis (DEA) technique. The analysis performs regressions where these also reveal that the bank efficiency index is influenced by various bank type-specific attributes. It also seems that tighter restrictions on bank activities are negatively associated with bank efficiency. Second stage analysis, which accounts for banking environment and bank-level characteristics, confirms these results. Findings Conventional banks are both more cost and revenue efficient than Islamic banks over the period under examination. The analysis also reveals that the bank efficiency index is influenced by bank-type attributes. Greater presence of fixed capital resources has positive effects on growth in both Islamic and conventional banking. The major constraints impeding Islamic banking growth include labour costs. The authors examine whether and how bank-type orientation affects the cost and revenue efficiency of conventional and Islamic banks. They find that post-crisis Islamic banks underperform their conventional counterparts on both accounts within a mixed banking system. Research limitations/implications This study did not include comparative data before the 2008 financial crisis. There is also a great deal of heterogeneity among Islamic banks in the samples that have been examined here and by other researchers and the constructed efficiency scores should be interpreted cautiously as divergent Islamic banks are pooled in the same samples. Practical implications This study identified factors that may help bank managers to improve their financial outlook by controlling revenue and cost efficiency profitability. These factors could as well help to understand how some indicators affect both cost and revenue efficiency, particularly in Islamic banking. It also seems that tighter restrictions on Islamic bank activities are negatively associated with bank efficiency. Islamic banks that directly compete with their conventional counterparts in the aftermath of the crisis are less efficient on both the cost and revenue frontiers. They are potentially hindered by the differential regulations of supervising authorities in dual banking systems. Social implications The authors provide recommendations regarding regulatory and other issues that are relevant to Islamic banking and further research is suggested. Findings are relevant to a variety of stakeholders (managers, policymakers and regulators). Islamic banking authorities could re-examine the benefits of partially moving to a more standardized/conventional system of banking by lifting some trading restrictions. In addition, developing and maintaining managerial skills is an indispensable instrument for the long-term endurance of any system. A related aspect is thus an effort to determine the holistic efficiency (including managerial) of Islamic banks as a guide for policymakers to improve managerial performance. Originality/value There is relatively limited empirical work that investigates the efficiency between Islamic and conventional banking in the aftermath of the crisis in the Gulf region despite the growing importance of this region on political and economic levels. The authors also examine the revenue efficiency measure often under-researched in the literature and particularly important for comparative studies. Overseas-owned banks have attained much higher infiltration levels in middle-eastern countries over the past decade. It has also been suggested that market penetration differences may also be related to bank efficiency concerns among countries and their financial systems as opposed to types of banks.

Movie Sentiment Analysis using Feature Dictionary and Multiview Light Semi Supervised Convolution Neural Network

Emotional information in film commentary is very important for emotional analysis. An emotional analysis that focuses on classifying opinions into positive and negative classes according to an emotional glossary is a study. Most existing research focuses on word synthesis and user evaluation, while users' attitudes toward feedback are ignored. To consider this point, this paper uses an emotional analysis and in-depth learning approach to examine the relationship between online film reviews, and this point is used for movie box revenue efficiency. In this paper, this work present a 11 different types of Feature Dictionary. It is modeled with information from sentences (i.e., reviews) and aspects simultaneously. First, Feature Dictionary is created with all aspects of the sentence. After obtaining the aspects, it utilize all data in the source domain and the target domain for training Multiview Light Semi Supervised Convolution Neural Network (MLSSCNN) classifier. To understand the predictive performance of this approach several performance metrics are used. The experimental result shows that the MLSSCNN provides a superior predictive effect than other classifier.