Executive Bonus Target Ratcheting: Evidence from the New Executive Compensation Disclosure Rules

This study investigates whether firms revise executive bonus compensation targets based on past performance. Studies in this area suffer from a lack of detailed information related to executive performance targets. Using mandatory disclosures of executive compensation information under the U.S. Securities and Exchange Commission's new disclosure rules, this study provides the first large‐sample evidence of bonus target ratcheting. There are three major findings: (i) executive bonus targets ratchet and they ratchet asymmetrically; (ii) the degree of target ratcheting and ratcheting asymmetry vary with executive equity incentives and investment opportunities; and (iii) performance relative to bonus target is serially correlated.     

Improving new product development using big data: a case study of an electronics company

Big data is becoming more important to the new product development (NPD) efforts of global firms. Although the term of big data is not new, very few studies have investigated how firms can harvest big data to facilitate NPD. The purpose of this article is to present the means by which big data can be used to assist firms in NPD to shorten the time to market, improving customers’ product adoption and reducing costs. This research is based on a two-step approach. First, we identified and analysed three world-leading firms that have successfully integrated big data in supporting their NPD. Then, the observations from the firms were used to determine the principle involved in leveraging big data to reduce product development lead times and costs. Given the exploratory nature of the research objective, a participant-observation case study is adopted in which during a 6-month period a NPD project in a fast moving high-tech industry was investigated. This study provides empirical confirmation for the three principles to big data supported NPD: (a) Autonomy; (b) Connection; and (c) Ecosystem. It is termed the ACE principles which we believe represent a paradigm shift to help firms unlock the power of big data and make NPD faster and less costly. This article provides guideline to firms in harvesting big data to better support their NPD: it allows organisations to launch new products to market as quickly as possible; it helps organisations to determine the weaknesses of the product earlier in the development cycle; it allows functionalities to be added to a product that customers are willing to pay a premium for, while eliminating features they do not want; and it identifies and then prioritises customer needs for specific markets.     

Is Job Insecurity Higher in Leveraged Buyouts?

This article assesses whether job insecurity is higher in leveraged buyouts (LBOs) than elsewhere. It draws on matched employer‐employee data from the British 2011 Workplace Employment Relations Study linked to data from the Centre for Management Buyout Research. The analysis finds no consistent evidence of higher job insecurity in LBOs as measured by workforce reduction practices (redundancy rates, job security/no‐compulsory redundancies policies and redundancy consultation), dismissal rates, labour use practices (non‐permanent employment contracts and outsourcing) and employees’ job security perceptions. Job insecurity is no higher in either current or former LBOs than elsewhere. Contrary to what might be expected, it is also no higher in private equity (PE)‐backed LBOs, management buy‐ins or high‐debt LBOs and there is only partial and weak evidence of higher job insecurity in short‐hold LBOs. Job insecurity is also no higher in perfect storm LBOs (PE‐backed management buy‐ins that are short‐holds with high‐debt). Concerns over the negative implications of LBOs for job security thus appear misplaced.     

What factors of early-stage innovative projects are likely to drive projects’ success? A longitudinal analysis of Korean entrepreneurial firms

Previous studies have identified the factors affecting successful technology commercialization as outcomes of R&D projects. However, most of them have used cross-sectional data, whereas there is a dearth of literature using longitudinal data analysis. Longitudinal analysis is essential for investigating the characteristics of early-stage innovative projects due to the inherent time lag between project evaluation and commercialization. Therefore, this study examines the early-stage project characteristics that can be used as meaningful evaluation criteria for predicting success, particularly in technology commercialization. We collected data on the ex-ante evaluation results and ex-post commercialization results of R&D projects pursued by entrepreneurial firms. We then conducted a logistic regression analysis and identified three market-related factors as significant in driving technology commercialization success in the early stages of technology development: market potential, commercialization plan, and market condition.     

Do Institutional Investors Enhance Accounting Earnings Attributes in the Korean Market?

This study examines whether the effectiveness of institutional monitoring depends on the economic conditions of emerging capital markets. We use trading volume data by investor type to compute a proxy for total institutional ownership. We then analyze the impact of the proxy variable on accounting earnings attributes and examine whether the association between the two depends on an expectation of market growth. We find that the effect of institutional monitoring decreases when market growth is expected to be low, implying that market growth may be a critical determinant of institutional investors’ long-term monitoring effectiveness in emerging capital markets.     

Effect of Restaurant Patrons' Regret and Disappointment on Dissatisfaction and Behavioral Intention

The objective of this study is to investigate the relationship among regret/disappointment, dissatisfaction, and behavioral intention in service failure situations at a restaurant. Even though there is a consensus regarding the positive relationship between regret/disappointment and customer dissatisfaction, unclear results still exist regarding the relationship between regret/disappointment and different types of behavioral intention. Thus, the present study attempts to clarify these fuzzy relationships. Specifically, this study aims to enhance understanding of the influence of regret and disappointment on behavioral intention (switching/negative WOM). The findings suggest that both regret and disappointment are significant determinants of customer dissatisfaction and switching/negative WOM. Further, the study results indicate that regret is an important predictor of switching intention, whereas disappointment is an important determinant of negative WOM. Finally, based on these findings, managerial implications for restaurant managers are discussed.