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The ability to analyze social action as it unfolds on micro time scales – particularly the 24-hour day – is central to understanding group processes. This chapter describes a new approach to this undertaking, which treats individuals’ involvement in specific activities at specific times as bases for: (1) sequential linkages between activities; as well as (2) connections to others who engage in similar action sequences. This makes it possible to examine the emergence and internal functioning of groups using existing network analysis techniques.

We illustrate this approach with a specific application – a quantitative and visual comparison of the daily activity patterns of employed and unemployed people. We use data from 13,310 24-hour time diaries from the 2010–2013 American Time Use Surveys.

Employed and unemployed people engage in significantly different types of activities and at different times. Beyond this, network analyses reveal that unemployed individuals experience much lower levels of synchrony with each other than do employed individuals and have much less organized action sequences. In short, there is a chronic lack of prevailing norms regarding how unemployed people organize the 24-hour day.

Future research that uses time-stamped data can employ network methods to analyze and visualize how group members sequence and synchronize social action. These methods make it possible to study how the structure of social action shapes group and individual-level outcomes.

This chapter develops a novel bootstrap procedure to obtain robust bias-corrected confidence intervals in regression discontinuity (RD) designs. The procedure uses a wild bootstrap from a second-order local polynomial to estimate the bias of the local linear RD estimator; the bias is then subtracted from the original estimator. The bias-corrected estimator is then bootstrapped itself to generate valid confidence intervals (CIs). The CIs generated by this procedure are valid under conditions similar to Calonico, Cattaneo, and Titiunik’s (2014) analytical correction – that is, when the bias of the naive RD estimator would otherwise prevent valid inference. This chapter also provides simulation evidence that our method is as accurate as the analytical corrections and we demonstrate its use through a reanalysis of Ludwig and Miller’s (2007) Head Start dataset.

We study Canadian national and provincial family income inequality from 1991 to 1997. We use special cases of generalized entropy measures, the Theil measures of inequality, since they are decomposable into between-provinces inequality and within provinces inequality. We draw statistical inferences from our findings by using the bootstrapping technique. We find that Canadian provinces have experienced differential trends in family income inequality over this period, a pattern that is masked when analyzing solely national trends. Changes in between-province family income inequality are found to be insignificant, indicating that the observed rise in overall inequality over this period is due to factors within provinces. Changes in within-province family income inequality are found to be significant. We further analyze two-way decompositions by province and education, and by province and age, to learn about the role of human capital and the life cycle in determining changes in family inequality among and within Canadian provinces.

When individual or household incomes are collected for administrative or scientific surveys, the accounting period is sometimes a month, sometimes a quarter, and sometimes a year. The accounting period likely affects the shape of the income distribution and the level of measured inequality. The present study systematically explores the sensitivity of inter-temporal and inter-regional inequality comparisons to the length of the accounting period.

Heavy-tailed distributions present a tough setting for inference. They are also common in industrial applications, particularly with internet transaction datasets, and machine learners often analyze such data without considering the biases and risks associated with the misuse of standard tools. This chapter outlines a procedure for inference about the mean of a (possibly conditional) heavy-tailed distribution that combines nonparametric analysis for the bulk of the support with Bayesian parametric modeling – motivated from extreme value theory – for the heavy tail. The procedure is fast and massively scalable. The work should find application in settings wherever correct inference is important and reward tails are heavy; we illustrate the framework in causal inference for A/B experiments involving hundreds of millions of users of eBay.com.

Field emergence poses an intriguing problem for institutional theorists. New issue fields often arise at the intersection of different sectors, amidst extant structures of meanings and actors. Such nascent fields are fragmented and lack clear guides for action; making it unclear how they ever coalesce. The authors propose that provisional social structures provide actors with macrosocial presuppositions that shape ongoing field-configuration; bootstrapping the field. The authors explore this empirically in the context of social impact investing in the UK, 2000–2013, a period in which this field moved from clear fragmentation to relative alignment. The authors combine different computational text analysis methods, and data from an extensive field-level study, to uncover meaningful patterns of interaction and structuration. Our results show that across various periods, different types of actors were linked together in discourse through “actor–meaning couplets.” These emergent couplings of actors and meanings provided actors with social cues, or macrofoundations, which guided their local activities. The authors thus theorize a recursive, co-constitutive process: as punctuated moments of interaction generate provisional structures of actor–meaning couplets, which then cue actors as they navigate and constitute the emerging field. Our model re-energizes the core tenets of new structuralism and contributes to current debates about institutional emergence and change.

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

This research explores perceptions of knowledge management processes held by managers and employees in a service industry. To date, empirical research on knowledge management in the service industry is sparse. This research seeks to examine absorptive capacity and its four capabilities of acquisition, assimilation, transformation and exploitation and their impact on effective knowledge management. All of these capabilities are strategies that enable external knowledge to be recognized, imported and integrated into, and further developed within the organization effectively. The research tests the relationships between absorptive capacity and effective knowledge management through analysis of quantitative data (n = 549) drawn from managers and employees in 35 residential aged care organizations in Western Australia. Responses were analysed using Partial Least Square-based Structural Equation Modelling. Additional analysis was conducted to assess if the job role (of manager or employee) and three industry context variables of profit motive, size of business and length of time the organization has been in business, impacted on the hypothesized relationships.

Structural model analysis examines the relationships between variables as hypothesized in the research framework. Analysis found that absorptive capacity and the four capabilities correlated significantly with effective knowledge management, with absorptive capacity explaining 56% of the total variability for effective knowledge management. Findings from this research also show that absorptive capacity and the four capabilities provide a useful framework for examining knowledge management in the service industry. Additionally, there were no significant differences in the perceptions held between managers and employees, nor between respondents in for-profit and not-for-profit organizations. Furthermore, the size of the organization and length of time the organization has been in business did not impact on absorptive capacity, the four capabilities and effective knowledge management.

The research considers implications for business in light of these findings. The role of managers in providing leadership across the knowledge management process was confirmed, as well as the importance of guiding routines and knowledge sharing throughout the organization. Further, the results indicate that within the participating organizations there are discernible differences in the way that some organizations manage their knowledge, compared to others. To achieve effective knowledge management, managers need to provide a supportive workplace culture, facilitate strong employee relationships, encourage employees to seek out new knowledge, continually engage in two-way communication with employees and provide up-to-date policies and procedures that guide employees in doing their work. The implementation of knowledge management strategies has also been shown in this research to enhance the delivery and quality of residential aged care.

The purpose of this chapter is to identify African financial management practices, highlight their origin and explain how they differ from their Western counterparts. The study identified indigenous African financial practices using literature review, archival sources and library research covering the five areas of Africa comprising Northern Africa, Eastern Africa, Central Africa Western Africa and Southern Africa. The study found out that pre-colonial indigenous African financial management features prevalent use of trade finance, trade credit management, investment management and accounting. While there is also evidence of modification of Western financial management practices to suit African contexts, it is on the whole scarce. This is suggestive of the fact that they were in existence in the first instance. The clear conclusion is that many indigenous African financial management practices pre-dated and foreshadowed their Western counterparts. Yet, it is confounding that this has been largely lost sight of, and both scholars and financial management practitioners depict the former as inferior. There is clearly a need to remedy this situation. Educators need to focus on incorporating ethno-finance concepts into the entire curricula chain from basic to higher education. The anchor point for such curricula is Ubuntu philosophy. Financial management practitioners, on their part, need to shed notions that the indigenous practices are inferior and seek to journalise their day-to-day work experiences to build a body of documented practice.