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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.

How and whether the rhythm, synchronization and sequence of firms' M&A and alliance activity over time impact firm performance is our core question. We seek to advance a temporal lens in the M&A and alliance discourse by explicitly incorporating time-associated theories, constructs and methods. A temporal view of M&A and alliance activity requires strategists to study fundamental questions related to when and under what conditions firms should accelerate, slow down and coordinate their M&A and alliance initiatives, whether firms' trajectory of M&A and alliance have discernible and distinctive patterns over time, and whether these initiatives demonstrate a temporal pattern that becomes an integrated part within firms' M&A and alliance routines that create a time-based source of competitive advantage. Using a sample of 57 small to medium-size firms in the global specialized pharmaceutical industry and their M&A and alliance activities for 19 years we find support for our temporal-based hypotheses.

This study examines the scheduling problem for a two-stage flowshop. All jobs are immediately available for processing and job characteristics including the processing times and due dates are known and certain. The goals of the scheduling problem are (1) to minimize the total flowtime for all jobs, (2) to minimize the total number of tardy jobs, and (3) to minimize both the total flowtime and the total number of tardy jobs simultaneously. Lower bound performances with respect to the total flowtime and the total number of tardy jobs are presented. Subsequently, this study identifies the special structure of schedules with minimum flowtime and minimum number of tardy jobs and develops three sets of heuristics which generate a Pareto set of bicriteria schedules. For each heuristic procedure, there are four options available for schedule generation. In addition, we provide enhancements to a variety of lower bounds with respect to flowtime and number of tardy jobs in a flowshop environment. Proofs and discussions to lower bound results are also included.

This contribution introduces sequence analysis to higher education research, an explorative technique aiming at detecting patterns, regularities and resemblance in time-ordered data. Thereby, it enables a holistic perspective on over-time developments and processes such as educational pathways or academic careers. In this contribution, the foundations and general logic of sequence analysis will be described. As an example, referring to the life course as a framing paradigm, sequence analysis is applied to reconstruct the study trajectories of a cohort of bachelor students in Germany. The potential of sequence analysis in three specific higher education research areas is outlined, that is, to study post-secondary education trajectories, academic careers and the development trajectories of higher education organizations. The conclusion discusses advantages and disadvantages, challenges and practicalities.

To explain how reading, rewinding a story in reverse order, and then rereading allows a reader to contextualize information, acquiring not only major themes and events but also details and other literacy characteristics of the literature selection.

A representation of sequencing structures is discussed including world-related, concept-related, inquiry-related, learning-related, and utilization-related. In addition, the instructional design aspects of backwards sequencing are discussed.

Just as a level or stud finder uses a back-and-forth approach for finding the most suitable position, so does the backwards sequential approach to reading comprehension. By slowing down and focusing on parts before the whole, students are more likely comprehend content.

The importance of prediction towards comprehension has been recognized for decades. However, using a learning design that features reading a story once, then revisiting the story structure components in backwards order, and finally reading it again, allows for precise and complete learning. This theory has research and pedagogical implications for students of all ages.

Understanding how dyadic negotiations and group decision processes evolve over time requires specifying the basic elements of process, modeling the configuration of those elements over time, and providing a theoretical explanation for that configuration. We propose a bead metaphor for conceptualizing the basic elements of the group negotiation process and then “string” the beads of behavior in a helix framework to model the process by which group negotiations evolve. Our theorizing draws on the group decision development literature (e.g. Bales, 1953; Poole, 1981, 1983a, b; Poole & Roth, 1989a, b) as well as on the negotiation process literature (e.g. Gulliver, 1979; Morley & Stephenson, 1977). Our examples are from our Towers Market studies of negotiating groups.

This paper examines the emergent and deliberate views in strategy making through, what we develop as, a sequence of thinking and acting. Combining the features of thinking and acting may enhance the organization's ability to achieve change, an ability that remains untapped unless it is accompanied by a change in mental models. Both action thinking emergent issues as well as thinking–acting deliberate issues may constitute triggering events, when contrasted with a previously agreed frame of reference. We develop a framework to show how thinking co-evolves with action in a succession of strategic activities, and within an agreed upon frame of reference. Our aim is to shed light on the circumstances under which deliberate or emergent modes take place throughout the strategy-making process. We claim that changes in strategic activities are determined by attention-triggering events, driven by both thinking and acting.

Management, over time, takes a series of specific strategic actions. As strategic actions we define actions aimed at influencing how the actor is related to other actors. We propose that when a strategic action is committed affects the outcome of the action. An important reason for this is that strategic actions over time can be regarded as interdependent sequences of actions. Timing and sequences may be more or less – or is not at all – preplanned by an actor. In a network perspective a focal actor is dependent on other actors that commit strategic actions. This creates interdependencies that vary over time, which a focal actor influences in a proactive, interactive and/or reactive way. The timing of strategic actions is a general, quite complex and elusive phenomenon to be handled in practice and theory. Despite its importance, very little research has been published.

Lechner and Miquel (2001) approached the causal analysis of sequences of interventions from a potential outcome perspective based on selection-on-observables-type assumptions (sequential conditional independence assumptions). Lechner (2004) proposed matching estimators for this framework. However, many practical issues that might have substantial consequences for the interpretation of the results have not been thoroughly investigated so far. This chapter discusses some of these practical issues. The discussion is related to estimates based on an artificial data set for which the true values of the parameters are known and that shares many features of data that could be used for an empirical dynamic matching analysis.