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The purpose of this paper is to investigate the effect of the control-ownership wedge of controlling shareholders (excess control) on the survival of French initial public offerings (IPOs).

This paper studies a large sample of 434 French IPOs. The empirical analysis uses the Cox proportional hazard and accelerated-failure-time models. Data are manually gathered from IPO prospectuses.

The findings support a positive relation between the control-ownership wedge and IPO survival time, indicating that survival is more likely in firms with high excess control levels. This result is consistent with the view that controlling shareholders with a large control-ownership wedge have incentives to preserve their private benefits of control by increasing firm survival chances. The findings also show that older IPOs are more likely to survive, while riskier and underpriced IPOs are more likely to delist.

The results provide a better understanding of the role of excess control in IPO survival. They also enrich the debate on the efficiency of the one-share-one-vote rule.

The research provides new insights into the role of agency conflicts in IPO survivability. In particular, it explores the effect of dominant shareholders with a control-ownership wedge on survival time.

A neglected area of research in ODC is the turnaround of poorly performing firms such as those under bankruptcy protection. We researched 142 companies that attempted reorganization under bankruptcy protection between 1983 and 2003. Firms deployed one or more of four distinct strategies to turnaround: rationalizing existing resources, developing existing resources, generating new resources, and investing in future resources. Firms that generated new resources, and developed and rationalized existing resources, had the highest probability of emergence. Interestingly firms that sustained their turnaround post-emergence invested in future resources in addition to generating, developing, and rationalizing resources. Implications for ODC are discussed.

The purpose of this paper is to analyse users’ attitudes towards online information retrieval and processing. The aim is to identify the characteristics of information that better capture the attention of the users and to provide evidence for the information retrieval behaviour of the users by studying online photo archives as information units.

The paper analyses a unique quasi-experimental data of photo archive access counts collected by the author from an online newspaper. In addition to access counts of each photo in 500 randomly chosen photo galleries, characteristics of the photo galleries are also recorded. Survival (duration) analysis is used in order to analyse the factors affecting the share of the photo gallery viewed by a certain proportion of the initial number of viewers.

The results of the survival analysis indicate that users are impatient in case of longer photo galleries; they lose attention faster and stop viewing earlier when gallery length is uncertain; they are attracted by keywords and initial presentation and they give more credit to specific rather than general information categories.

Results of the study offer applicable implications for information providers, especially on the online domain. In order to attract more attention, entities can engage in targeted information provision by taking into account people’s attitude towards information retrieval and processing as presented in this paper.

This paper uses a unique data set in a quasi-experimental setting in order to identify the characteristics of online information that users are attracted to.

The aim of this paper is to review the literature on the prediction of cutting tool life. Tool life is typically estimated by predicting the time to reach the threshold flank wear width. The cutting tool is a crucial component in any machining process, and its failure affects the manufacturing process adversely. The prediction of cutting tool life by considering several factors that affect tool life is crucial to managing quality, cost, availability and waste in machining processes.

This study has undertaken the critical analysis and summarisation of various techniques used in the literature for predicting the life or remaining useful life (RUL) of the cutting tool through monitoring the tool wear, primarily flank wear. The experimental setups that comprise diversified machining processes, including turning, milling, drilling, boring and slotting, are covered in this review.

Cutting tool life is a stochastic variable. Tool failure depends on various factors, including the type and material of the cutting tool, work material, cutting conditions and machine tool. Thus, the life of the cutting tool for a particular experimental setup must be modelled by considering the cutting parameters.

This submission discusses tool life prediction comprehensively, from monitoring tool wear, primarily flank wear, to modelling tool life, and this type of comprehensive review on cutting tool life prediction has not been reported in the literature till now. The future suggestions provided in this review are expected to provide avenues to solve the unexplored challenges in this field.

Prior literature has widely established that the design of storage locations impacts order picking task performance. The purpose of this study is to investigate the performance impact of unit loads, e.g. pallets or rolling cages, utilized by pickers to pack products after picking them from storage locations.

An empirical analysis of archival data on a manual order picking system for deep-freeze products was performed in cooperation with a German brick-and-mortar retailer. The dataset comprises N = 343,259 storage location visits from 17 order pickers. The analysis was also supported by the development and the results of a batch assignment model that takes unit load selection into account.

The analysis reveals that unit load selection affects order picking task performance. Standardized rolling cages can decrease processing time by up to 8.42% compared to standardized isolated rolling boxes used in cold retail supply chains. Potential cost savings originating from optimal batch assignment range from 1.03% to 39.29%, depending on batch characteristics.

This study contributes to the literature on factors impacting order picking task performance, considering the characteristics of unit loads where products are packed on after they have been picked from the storage locations. In addition, it provides potential task performance improvements in cold retail supply chains.

Tax risk refers to the uncertainty of future corporate taxation. Tax reform is a key issue in major current tax system adjustments that seriously affect a firm's tax risk. In response to changes in the economic environment, many countries are actively executing tax reform. Long-term reforms implemented for a smooth transition may instead increase corporate risk. This study examines the relationship among tax risk, tax reform and investment timing.

Selecting the Shanghai Stock Exchange and Shenzhen Stock Exchange A-share listed companies' panel data from 2008 to 2017, the paper used survival analysis and the propensity score matching-difference in difference models.

The results show that a higher corporate tax risk results in more deferred investments, which are further examined using the latest Chinese value-added tax reform as a natural experiment.

The conclusion serves as an important reference for governments to balance reform time and to support enterprises in effectively identifying and managing tax risk under tax reform.

The purpose of this paper is to investigate the competing effects of brand community participation, which should enhance loyalty to both the brand and to already-owned products, against switching costs, which should make consumers sensitive about the financial costs associated with new products.

Using the participation and weekly adoption data from 7,411 members in two brand communities and one product category forum over a six-month period, switching costs were computed for each member using 10 years of product release and pricing data.

Consistent with prior research, switching costs had a significant effect on reducing product adoption. Brand community participation also had a significant effect on overcoming switching costs. However, these main effects were qualified by an interaction, such that the most active participants were more likely to buy the new product when switching costs were higher.

Most importantly, these findings provide unique insights into financial switching costs and demonstrate ways in which brand community participation provides a way to mitigate switching costs for consumers who would most be affected by them.

The purpose of this paper is to investigate the effect of executive severance contract maturity policies on the likelihood of forced turnover and the length of tenure for CEOs who are forced from their positions.

The paper utilizes logistic and accelerated failure time models to test the hypothesis that severance contracts decrease information asymmetries resulting in an increased likelihood of forced turnover and a shortened tenure for those CEOs who are forced out.

The results provide evidence that fixed‐term severance contracts increase the likelihood of forced tenure and decrease the length of tenure for CEOs who experience a forced turnover during the period, while time‐independent contracts do not.

The limitation is the possibility that an omitted variable jointly determines the likelihood of the presence of a severance contract and the effect on forced turnover. Future research should investigate other possibilities beyond the CEO coming from outside of the firm.

The findings confirm that the maturity policies of severance contracts affect forced turnover. The results suggest that there may be a benefit in designing severance contracts to expire to encourage more efficient turnover of underperforming CEOs.

This paper contributes to the empirical corporate finance and accounting literature by differentiating between forced and unforced turnover when analyzing the effects of severance contracts and demonstrating that the time dimension of severance contracts may provide the desired result of encouraging the identification of CEO‐firm mismatches.

The purpose of this paper is to examine the survivability of 810 reverse splits during the 1995-2006 period and show that companies that undertake reverse stock splits often fail within a relatively short time following the split.

Applying both a logit model and an adapted version of the Hensler et al. (1997) accelerated failure time model to 810 reverse splits during the 1995-2006 period, the authors are the first to study the survivability of reverse split companies.

The paper finds that the market reaction to the reverse split on the ex-date is an important predictor of the likelihood of survival and of survival time. The paper finds that the likelihood of survival also depends on firm size, pre-split firm returns, and the post-split share price level. The paper finds that post-split survival time also depends on firm size, pre-split operating performance as measured by return on assets, pre-split firm returns, leverage, and the post-split share price level.

The study may be of interest to investors considering investing in stocks that have undergone reverse splits.

The research sheds light on which reverse splitting firms are most likely to survive and for how long.

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.

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.

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.

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.

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.

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.