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This chapter first analyzes how the data-cleaning process affects the share of missing values in the extracted European and North American datasets. It then moves on to examine how three different approaches to treat the issue of missing values, Complete Case, Multiple Imputation Chained Equations (MICE), and K-Nearest Neighbor (KNN) imputations affect the number of firms and their average lifespan in the datasets compared to the original sample and assessed across different SIC industry divisions. This is extended to consider implied effects on the distribution of a key performance indicator, return on assets (ROA), calculating skewness and kurtosis measures for each of the treatment methods and across industry contexts. This consistently shows highly negatively skewed distributions with high positive excess kurtosis across all the industries where the KNN imputation treatment creates results with distribution characteristics that are closest to the original untreated data. We further analyze the persistency of the (extreme) left-skewed tails measured in terms of the share of outliers and extreme outliers, which shows consistent and rather high percentages of outliers around 15% of the full sample and extreme outliers around 7.5% indicating pervasive skewness in the data. Of the three alternative approaches to deal with missing values, the KNN imputation treatment is found to be the method that generates final datasets that most closely resemble the original data even though the Complete Case approach remains the norm in mainstream studies. One consequence of this is that most empirical studies are likely to underestimate the prevalence of extreme negative performance outcomes.

All firms operating in the global economy are exposed to a multitude of risks including financial crisis, cyberattack, social instability, governance failure, extreme weather events, etc. As a consequence, international organizations assume many (new and evolving) exposures that must be addressed, where some firms are able to adjust and thrive against these adverse odds, whereas many others fail. It appears like some (a few) firms are able to repeatedly outperform the market, where a great many of them struggle, and quite a few register negative returns every year. As a consequence, the authors typically observe leptokurtic negatively skewed distributions of financial returns with extreme negative tails of poor performing firms, where the performance data fall way beyond the requirements of a normal distribution. The authors investigate this phenomenon based on a comprehensive dataset of European firms retrieved from Compustat Global for the 25-year period 1995–2019. The analysis shows that there is indeed a consistent pattern of many underperforming firms across different industry classifications and time intervals and a few outperformers. This provides evidence of a regularly observed phenomenon that often is overlooked in mainstream management studies. The results have implications for academic research that often relies on assumptions of data normality in statistical analysis and for corporate management that has to deal with a risk-prone business environment.

It is not any exaggeration to state Dubai as a global city. Furthermore, the Dubai World Trade Centre (DWTC) acts as a gateway for international visitors into this city. Starting from a business center in 1979, the tower has grown to house more than 3 million attendees annually. The tower expanded from its 39-story establishment to a full-blown project encompassing concourses, venues, and business offices. The 40-years’ experience enables the DWTC to establish itself as the chief organizer of more than 500 events in a year. Furthermore, relying on its excellent training program, customer-centric approach and active leadership participation, the DWTC has molded many leaders that solve futuristic problems. DWTC has driven economic growth in the local business environment for ancillary services as well. DWTC facilitates almost 3.3% of Dubai’s GDP, thus, putting things into perspective concerning its contribution to the local economy. Hence, DWTC acts as a beacon of light for the bright prospects of Dubai’s future, therefore, cementing its position in world trade.

Purpose – This chapter examines disputes produced by two young children during computer game playing and considers how the disputes were related to the children's ongoing activity.

Methodology/approach – The study is framed by ethnomethodology and conversation analysis. Sequential analysis of recorded data details the mutual production of disputes during talk and interaction.

Findings – The analysis establishes how the children made each other accountable to the agreed-upon way of playing the game after one child offered to show the other how to play. Conflict developed during the game and disputes built upon previous disputes, especially in relation to claims made about knowing how to play.

Research implications – The disputes here are best understood in relation to how disagreement was avoided initially but then emerged as the gaming progressed. Examining disputes in the course of computer activity shows how the children turn agreement into disagreement over time.

Social implications – This study establishes some of the ways that disputes arise out of young children's social interactions during computer game playing and how disputes are related, or not, to shared understandings of what is going on moment by moment in the game.

Originality – Overall, this chapter provides a detailed sequential analysis across computer activity and establishes how the children's disputes challenge the order of game playing as the game progresses.

To describe the role one classroom writing community played in shaping students’ understandings of the analytical writing genre; and to discuss the impact the community had on students’ developing academic writing identities.

While research has demonstrated the impact of classroom writing communities on student writing practices and identities at the elementary level (Dyson, 1997) and for secondary students engaged in fiction writing (Halverson, 2005), less is known about the role classroom writing communities may play for secondary students who are learning to write in academic discourses. This chapter explores the practices of one such classroom community and discusses the ways the community facilitated students’ introduction to the discourse of analytical writing.

The teacher turned the classroom writing community into an authentic audience, and in so doing, he developed students’ understandings of the analytical writing genre and their growing identities as academic writers. First, he used the concept of immediate audience (i.e., writing to persuade real readers) as the primary rationale for students to follow the outlined expectations for analytical writing. Second, he used inquiry discussions around student work (i.e., interacting with other members of the writing community) to prepare students for a future audience of prospective independent school English classrooms.

By turning the classroom writing community into an authentic audience through inquiry discussions, teachers can develop students’ deep and flexible understandings of a potentially unfamiliar writing genre. Furthermore, by employing the classroom writing community as a support for moving students through moments of struggle, teachers implicate students’ expertise as academic writers, thereby facilitating their willingness to take on academic writing identities.