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Article

Yuangen Lai and Jianxun Zeng

The purpose of this paper is to discuss issues related to customer churn behavior in digital libraries (DLs) and demonstrate the successful application of Survival Analysis

Abstract

Purpose

The purpose of this paper is to discuss issues related to customer churn behavior in digital libraries (DLs) and demonstrate the successful application of Survival Analysis for understanding customer churn status and relationship duration distribution between customers and libraries.

Design/methodology/approach

The study applies non-parametric methods of Survival Analysis to analyze churn behaviors of 8,054 customers from a famous Chinese digital library, and a cluster method to make customer segmentation according to customer behavioral features.

Findings

The customer churn rate of the given library is very high, so as to the churn hazard in early three months after customer's registration on the web site of the library. There is clear difference in both customer survival time and churn hazard among customer groups. It is necessary to strengthen customer churn analysis and customer relationship management (CRM) for DLs.

Research limitations/implications

The studied samples are mainly based on customers from one digital library and some hypotheses have not been strictly proven due to the absence of relevant empirical researches.

Practical implications

This study provides a reasonable basis for decision making about CRM in DLs.

Originality/value

Most previous researches about information behavior concentrate on information seeking behavior in DLs, seldom discuss customer switching behavior. The paper discusses issues related to customer churn analysis and illustrates the adaptation of Survival Analysis to understand customer churn status and relationship duration distribution in DLs.

Details

Program, vol. 48 no. 4
Type: Research Article
ISSN: 0033-0337

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Article

Scott Dellana and David West

The purpose of this paper is to apply survival analysis, using Cox proportional hazards regression (CPHR), to the problem of predicting if and when supply chain (SC…

Abstract

Purpose

The purpose of this paper is to apply survival analysis, using Cox proportional hazards regression (CPHR), to the problem of predicting if and when supply chain (SC) customers or suppliers might file a petition for bankruptcy so that proactive steps may be taken to avoid a SC disruption.

Design/methodology/approach

CPHR is first compared to multiple discriminant analysis (MDA) and logistic regression (LR) to assess its suitability and accuracy to SC applications using three years of financial quarterly data for 69 non-bankrupt and 74 bankrupt organizations. A k-means clustering approach is then applied to the survival curves of all 143 organizations to explore heuristics for predicting the timing of bankruptcy petitions.

Findings

CPHR makes bankruptcy predictions at least as accurately as MDA and LR. The survival function also provides valuable information on when bankruptcy might occur. This information allows SC members to be prioritized into three groups: financially healthy companies of no immediate risk, companies with imminent risk of bankruptcy and companies with intermediate levels of risk that need monitoring.

Originality/value

The current paper proposes a new analytical approach to scanning and assessing the financial risk of SC members (suppliers or customers). Traditional models are able to predict if but not when a financial failure will occur. Lacking this information, it is impossible for SC managers to prioritize risk mitigation activities. A simple decision rule is developed to guide SC managers in setting these priorities.

Details

The Journal of Risk Finance, vol. 17 no. 2
Type: Research Article
ISSN: 1526-5943

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Book part

David S. DeGeest and Ernest H. O’Boyle

To review and address current approaches and limitations to modeling change over time in social entrepreneurship research.

Abstract

Purpose

To review and address current approaches and limitations to modeling change over time in social entrepreneurship research.

Methodology

The article provides a narrative review of different practices used to assess change over time. It also shows how different research questions require different methodologies for assessing changes over time. Finally, it presents worked examples for modeling these changes.

Findings

Our review suggests that there is a lack of research in social entrepreneurship that takes into account the many different considerations for addressing how time influences outcomes.

Originality/value

This chapter introduces an analytic technique to social entrepreneurship that effectively models changes in predictors and outcomes even when data are non-normal or nested across time or levels of analysis.

Details

Social Entrepreneurship and Research Methods
Type: Book
ISBN: 978-1-78441-141-1

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Article

Bharat A. Jain and Charles L. Martin Charles L. Martin Jr.

This study examines the issue of whether audit quality contracted by issuers at the time of going public is associated with post‐IPO survival. Survival analysis

Abstract

This study examines the issue of whether audit quality contracted by issuers at the time of going public is associated with post‐IPO survival. Survival analysis methodology is applied to estimate the probability of post‐IPO time to failure as a function of audit quality. Through estimation of the Cox‐Proportional Hazards models, we find that audit quality is significantly related to post‐IPO time to failure both in isolation and in the presence of other covariates that influence firm survival. Further, the association between audit quality and post‐IPO survival is stronger when investment bank prestige is low.

Details

Review of Accounting and Finance, vol. 4 no. 4
Type: Research Article
ISSN: 1475-7702

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Article

Carl R. Borgia, Philip H. Siegel and Dennis Ortiz

– The purpose of this study is to consider the effect of an internship experience on tax accountants’ professional performance.

Abstract

Purpose

The purpose of this study is to consider the effect of an internship experience on tax accountants’ professional performance.

Design/methodology/approach

It uses survival analysis, a dynamic methodology that allows for more precise modeling than static traditional methods used to study promotion and turnover rates in the past. The hypotheses were tested using a longitudinal database obtained from the human resource departments of regional Certified Public Accountant firms located in the southeastern and mid-south areas of the USA.

Findings

Results were mixed. As in previous studies on the effects of internships on subsequent professional performance, tax accounting professionals with a master’s degree and prior internship experience had significantly faster promotion rates than those professionals with a master’s degree and no internship experience. However, tax professionals with a master’s degree and prior internship experience did not demonstrate a significant difference in turnover rate when compared to the no-internship group.

Practical implications

This research provides evidence that students, employers and institutions of higher education can use to guide them in their decisions regarding the effects of structured internships on professional performance – in this case, the professional performance of tax accountants.

Originality/value

Previous research on tax professionals’ performance and internship experience made use of static research methodologies. This study uses the more dynamic methodology of survival analysis to see if different findings result.

Details

Accounting Research Journal, vol. 27 no. 3
Type: Research Article
ISSN: 1030-9616

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Article

Nil Gunsel

The purpose of this paper is to investigate the determinants of the timing of bank failure in North Cyprus over the period of 1984‐2002 using a discrete‐time logistic…

Abstract

Purpose

The purpose of this paper is to investigate the determinants of the timing of bank failure in North Cyprus over the period of 1984‐2002 using a discrete‐time logistic survival analysis.

Design/methodology/approach

The empirical methodology employed in the paper allows for the determination of the factors that influence the time to bank failure. The model links the time of bank failure to a set of bank‐specific factors and macro‐environment that may have exacerbated the internal troubles of the financial institutions.

Findings

An empirical examination of the results on survival analysis reveal that the three variables, namely: low asset quality (total loan as a percentage of total assets), low liquidity (total liquid asset as a percentage of total assets), and high credit extended to the private sector (ratio of the private credit to gross domestic product) are the main factors that explain the survival time of banks in North Cyprus.

Research limitations/implications

For further research this paper may better distinguish time to bank failure if it extends the time period and if it uses exchange pressure from Turkey that may have a direct effect on bank failure in North Cyprus.

Practical implications

Nowadays bank failure is an important problem in the world. Using time technique to investigate bank failure will help to learn the factors that determine time to bank failure, which will further help to take precautions and prevent the cost of bank failure.

Originality/value

The analysis would appear to be the first to provide evidence and investigate the time to bank failure in the North Cyprus banking sector.

Details

The Journal of Risk Finance, vol. 11 no. 1
Type: Research Article
ISSN: 1526-5943

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Article

German Gemar, Ismael P. Soler and Vanesa F. Guzman-Parra

This study aims to examine variables influencing resort hotels’ survival in Spain, which had not previously been analysed. In this country, determining whether the reasons…

Abstract

Purpose

This study aims to examine variables influencing resort hotels’ survival in Spain, which had not previously been analysed. In this country, determining whether the reasons resort hotels close are different from other hotels could be imperative to resort hotels’ survival.

Design/methodology/approach

The survival analysis used Cox’s semi-parametric proportional hazards regression to determine which variables influence hotel closure and how much each variable increases risk of closure.

Findings

Resort hotel closure depends on hotel size, location, executive management and the business cycle. Survival is not affected by hotel type or financial structure.

Research limitations/implications

While this methodology is common in business survival analyses, it has seldom been applied to hotels and has never been used to study the survival of resort hotels.

Practical implications

Companies need to rethink the location of new hotels. For already-built facilities, good management practices are strategically important for resort hotels’ survival.

Originality/value

This paper explores the reasons why resort hotels survive. The study’s selection of variables and methodology and its conclusions are unique.

Details

International Journal of Contemporary Hospitality Management, vol. 31 no. 4
Type: Research Article
ISSN: 0959-6119

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Article

A.B. Khalaf, Y. Hamam, Y. Alayli and K. Djouani

Studying the availability of medical equipment based on various maintenance types has been a major concern for hospitals. Most of the methodologies used are empirical and…

Abstract

Purpose

Studying the availability of medical equipment based on various maintenance types has been a major concern for hospitals. Most of the methodologies used are empirical and few are based on mathematical modelling. The objective of this paper is to present a mathematical maintenance model that analyses the effect of maintenance on the survival probability of medical equipment based on maintenance history and age of that equipment.

Design/methodology/approach

A global model is proposed to measure the probability of equipment being available using real data extracted from maintenance history of infusion pumps and ventilators and analysed using Matlab. To confirm the validity of the developed model, the survival analysis approach is used to develop a model that measures the survival of equipment as a function of maintenance and age of equipment. The method is first tested using simulated data and the findings confirm the validity of the proposed approach.

Findings

The analysis using survival approach reveals that conducting preventive maintenance (PM) on the selected medical equipment had an impact on survival of equipment. However, the manufacturer's recommended PM intervals do not correlate to the failure rate encountered. This will contribute to the debate on PM manufacturer's recommended intervals and might lead to the revision of maintenance strategies implemented by hospitals and clinical engineering (CE) practitioners.

Research limitations/implications

Although the data collected for the infusion pumps were quite sufficient, that collected for the ventilators were more limited. The major difficulty is that of the availability of historical maintenance data and the effect of user errors may cause uncertainty in the analysis. A closer collaboration with the medical professional should facilitate the recording and access to such information.

Practical implications

The use of mathematical modelling to analyse the effect of maintenance on the survival of medical equipment is a beneficial tool that is not exploited in the medical equipment industry. It will provide CE practitioners with scientific tool to analyse the effect of PM on the survival of medical equipment.

Originality/value

This paper presents a mathematical approach to analyse the effect of maintenance on the survival of medical equipment, which is crucial in the assessment of maintenance strategies implemented in the medical equipment industry.

Details

Journal of Engineering, Design and Technology, vol. 11 no. 2
Type: Research Article
ISSN: 1726-0531

Keywords

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Article

Jake Ansell, Tina Harrison and Tom Archibald

To demonstrate the successful use of lifestage segmentation and survival analysis to identify cross‐selling opportunities.

Abstract

Purpose

To demonstrate the successful use of lifestage segmentation and survival analysis to identify cross‐selling opportunities.

Design/methodology/approach

The study applies lifestyle analysis and Cox's regression analysis model to behavioural and demographic data describing 10,979 UK customers of a large international insurance company.

Findings

There are clear differences between the lifestage segments identified with respect to customer characteristics affecting the likelihood of a second purchase from the company and the timeframes within which that is likely to take place. The “mature” segments appear to offer greater opportunities for retention and cross‐selling than the “younger” segments.

Research limitations/implications

The study was limited by the type of data available for analysis, which related mainly to life insurance and pension products characterised by low transaction frequency. Different results might be expected for banking or credit‐and‐loan products. The findings could be enhanced by incorporating a wider range of customer characteristics into the analysis.

Practical implications

The findings show clear differences in behaviour across the segments identified, providing a basis on which marketing planners might differentiate marketing and communication strategies for particular products market segments.

Originality/value

The paper illustrates the adaptation of survival analysis methodology, familiar in other disciplines but comparatively rare in marketing, to the cross‐selling of financial services. It shows how planners cannot only identify customers most likely to repurchase but also predict the timeframe in which that will take place.

Details

Marketing Intelligence & Planning, vol. 25 no. 4
Type: Research Article
ISSN: 0263-4503

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Article

Patrick Mair, Horst Treiblmaier and Paul Benjamin Lowry

The purpose of this paper is to present competing risks models and show how dwell times can be applied to predict users’ online behavior. This information enables…

Abstract

Purpose

The purpose of this paper is to present competing risks models and show how dwell times can be applied to predict users’ online behavior. This information enables real-time personalization of web content.

Design/methodology/approach

This paper models transitions between pages based upon the dwell time of the initial state and then analyzes data from a web shop, illustrating how pages that are linked “compete” against each other. Relative risks for web page transitions are estimated based on the dwell time within a clickstream and survival analysis is used to predict clickstreams.

Findings

Using survival analysis and user dwell times allows for a detailed examination of transition behavior over time for different subgroups of internet users. Differences between buyers and non-buyers are shown.

Research limitations/implications

As opposed to other academic fields, survival analysis has only infrequently been used in internet-related research. This paper illustrates how a novel application of this method yields interesting insights into internet users’ online behavior.

Practical implications

A key goal of any online retailer is to increase their customer conversation rates. Using survival analysis, this paper shows how dwell-time information, which can be easily extracted from any server log file, can be used to predict user behavior in real time. Companies can apply this information to design websites that dynamically adjust to assumed user behavior.

Originality/value

The method shows novel clickstream analysis not previously demonstrated. Importantly, this can support the move from web analytics and “big data” from hype to reality.

Details

Internet Research, vol. 27 no. 3
Type: Research Article
ISSN: 1066-2243

Keywords

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