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Stretch Yourself: Benefits and Burdens of Job Crafting That Goes Beyond the Job
No full textAs employees cannot always readily stretch their competencies and professional identity on the job through regular job crafting, we ask the question: are there alternative ways of crafting inside organizations through which people can stretch themselves? Using grounded theory methods, we step into the shoes of federal employees active in Open Opportunities, a digital market for temporary assignments in the U.S. federal government. We find that employees use such temporary assignments to craft a liminal space in which they can explore new skills, establish new professional ties, and claim new professional identities unavailable in their full-time jobs. However, due to its visibility, this way of crafting can also generate substantial supervisory pressures resisting it. These pressures may induce an image cost, and trigger increased frustration, stress, and strain in people’s jobs. As we describe this new job crafting pattern, we pay attention to both its benefits and burdens, and the impact thereof on people’s efforts to stretch themselves at work. We discuss the theoretical and practical implications of our study and its consequences for future research on job crafting, professional identity development, and the future of work.Belgian Federal Public Service of Policy and Support - We want to extend our special thanks to Lisa Nelson, director of strategic planning for Open Opportunities, for enabling the study. This research was supported by the Belgian Federal Public Service of Policy and Support
Sharing the wealth: Examining executive compensation in Europe
No full textResearchers have pointed to the need for more study of CEO compensation in Europe. Even though a single article will not be able to solve this need, we want to share a number of insights, relevant for a global audience, based on the dataset of the executive remuneration research centre of the Vlerick Business School in Belgium
Do People Understand the Benefit of Diversification?
No full textDiversification—investing in imperfectly correlated assets—reduces volatility without sacrificing expected returns. Although the expected return of a diversified portfolio is the weighted average return of its constituent parts, the variance of the portfolio is less than the weighted average variance of its constituent parts. Our results suggest that very few people have correct statistical intuitions about the effects of diversification. The average person in our data sees no benefit of diversification in terms of reducing portfolio volatility. Many people, especially those low in financial literacy, believe diversification actually increases the volatility of a portfolio. These people seem to believe that the unpredictability of individual assets compounds when aggregated together. Additionally, most people believe diversification increases the expected return of a portfolio. Many of these people correctly link diversification with the concept of risk reduction but seem to understand risk reduction to mean greater returns on average. We show that these beliefs can lead people to construct investment portfolios that mismatch investors’ risk preferences. Furthermore, these beliefs may help explain why many investors are underdiversified.
This paper was accepted by Yuval Rottenstreich, decision analysis
Advances in flexible models and efficient statistical procedures for heavy-tailed and asymmetric data
No full textLeveraging fine-grained mobile data for churn detection through Essence Random Forest
No full textThe rise of unstructured data leads to unprecedented opportunities for marketing applications along with new methodological challenges to leverage such data. In particular, redundancy among the features extracted from this data deserves special attention as it might prevent current methods to benefit from it. In this study, we propose to investigate the value of multiple fine-grained data sources i.e. websurfing, use of applications and geospatial mobility for churn detection within telephone companies. This value is analysed both in substitution and in complement to the value of the well-known communication network. What is more, we also suggest an adaptation of the Random Forest algorithm called Essence Random Forest designed to better address redundancy among extracted features. Analysing fine-grained data of a telephone company, we first find that geo-spatial mobility data might be a good long term alternative to the classical communication network that might become obsolete due to the competition with digital communications. Then, we show that, on the short term, these alternative fine-grained data might complement the communication network for an improved churn detection. In addition, compared to Random Forest and Extremely Randomized Trees, Essence Random Forest better leverages the value of unstructured data by offering an enhanced churn detection regardless of the addressed perspective i.e. substitution or complement. Finally, Essence Random Forest converges faster to stable results which is a salient property in a resource constrained environment
Intra-industry diversification effects under firm-specific contingencies on the demand side
No full textHow do firm-specific, demand-related factors influence the relationship between intra-industry diversification (IID) and performance? Recent findings regarding the performance effects of IID depict a complex picture with curvilinear relationships and several contingencies. However, firm-specific contingencies on the demand side have remained unexplored. We analyze how IID relates to firm performance (market share) in the German automotive industry using panel data between 1999 and 2008. We specifically focus on a firm's high-quality brand image as a demand-side contingency. We find support for our hypotheses of complex curvilinear relationships as well as for moderating effects of brand quality. Our results have significant theoretical implications for the IID literature
Customer churn prediction using machine learning and customer lifetime value analysis at Eurotel
No full textEvery CFO should invest in getting to know the organisation’s customers. After all, building long-term and valuable customer relationships is an important driver of value creation. This case study explores how machine learning and predictive analytics can be used to develop a deeper understanding of customer behaviour and to enhance customer profitability. The case study consists of two parts: part A, customer churn prediction using machine learning, and part B, customer lifetime value analysis. In part A, the focus is on using machine learning to predict customer churn at Eurotel, a Belgian telecommunications start-up. The participants will learn how to pre-process raw customer data and will use different modelling techniques to predict customer churn. Furthermore, they will learn how to select the right model based on business relevance and performance. In part B, the participants will use the insights derived in the first part to analyse the customer lifetime value of the different Eurotel customers. This will serve as input for a marketing analysis. The goal is to determine which customer and product segments of Eurotel are most valuable and to strategically select the right marketing campaigns to target those segments. The participants will learn how to implement a customer lifetime value analysis and how the resulting information can be used to design an effective marketing campaign. The participants will also learn how they can implement the analysis in python
Academy of Management Proceedings
No full textDrawing on the organizational justice literature and the construct of necessary evil, this paper examines the experience of layoffs from an under-researched perspective - managers. The managers often play conflicting roles in an organizational necessary evil; they are both witnesses to and survivors of the harm caused to employees by layoffs. Applying insights from cognitive appraisal theory, we propose a serial mediation model whereby the effect of procedural justice in a layoff context on managerial exit intentions is serially mediated by managerial feelings of control and well-being. We test and confirm our hypotheses using survey data from 144 managers in a large European telecommunications company that had conducted layoffs. In line with cognitive appraisal theory, our work extends current research on the importance of organizational justice as a resource for managers in the context of necessary evils. We also extend understanding of necessary evils and how their burden can be made less severe to managers – both for those tasked with them and observing them - and confirm the positive effects of procedural justice for managers’ health and exit intentions
Academy of Management Annual Meeting Proceedings.
No full textIn the context of intense global stakeholder pressures to improve female representation in the executive suite, we examine the speed of advancement and exit of first time executive directors around the world. We make two inter-related arguments. First, we argue that while normative pressures from global stakeholders have created a gender premium for women in the form of lower age at the time of appointment vis-à-vis male executive directors, appointed women are also penalized in the form of quicker exits from these positions because of their lower age. Second, we contend that this gender premium and penalty is contingent on the local gender norms in a society such that lower gender parity leads to a higher premium and penalty for these women. Results based on a sample of 15,202 first time executive directors from 6,452 firms in 33 countries largely support our theoretical predictions