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Properly conceived, conducted and interpreted, motivation research can be an extremely powerful management tool, designed to help the manufacturer or advertiser to sell more goods. Its aim is to expose the market situation, explain it and suggest courses of action which will lead to desired changes. It is a way of looking at a problem rather than a collection of specialist techniques and is strictly practical. Hence it can be used alongside other market research tools for the solution of marketing problems and can be applied to a wide range of business activities. Much of its development has been in the advertising field but it can also help in the formulation of production policy, solving packaging problems and marketing operations. It is examined here in all these contexts. The idea of motivation research, the reasons for its use and the techniques by which to apply it are discussed, as well as the pitfalls that are likely to occur. New and imaginary case studies are used throughout to illustrate points. A review of the subject literature is included.

The paper aims to explicate the systematic creation of social and ecological scarcities within an absolutely monetised economy and derives the necessity to change the “rules of the game” for doing business towards sustainability. Therefore, a model of human behaviour is developed to explain, on the one hand, sustainability‐hostile behaviour and to contribute to sustainability‐supporting behaviour and “rules of the game” in dynamic interactions, on the other hand.

A model of human behaviour is developed, integrating socio‐scientific insights as well as socio‐biological and evolutionary‐psychological findings. The emergence of human behaviour is conceptualised as an interactive process using the theory of nested control loops including constructivist impulses.

Human behaviour is regarded as the result of three constituting components: cultural shaping (cultural artefacts, education, socialization, enculturation), genetic predisposition (pattern recognition based on instincts, needs, drives, etc.), and situational correctives. These components are connected and interlinked in an “inner model” with the help of four feedback loops (constructivist feedback loop, emergency and reflex feedback loop, interaction feedback loop, and adaptation feedback loop) in the unity of eco‐ and psychosphere.

The developed model of behaviour offers a relatively high degree of abstraction. Further research should consider in detail the constituting components of the model and scrutinise the underlying presumptions and conclusions.

Conclusions arise for designing institutional arrangements, on the one hand, and management approaches and dialogue forms for shaping work processes in the dynamic interaction of individuals and institutions (companies and their units, NGOs, financial institutions, insurance companies, public authorities, etc.), on the other hand.

Because of the cybernetic interlock of the three constituting impulses for human behaviour cultural factors, genetic predispositions, and situational influences, the presented model provides possibilities to explain sustainability‐hostile as well as sustainability‐supporting behaviour within the dynamic interaction of individuals and institutions. The target group includes social scientists and economists as well as managers and persons with practical experience in business and politics.

Human group behavior is the driving force behind many complex social and economic phenomena. Few studies have integrated multi-dimensional travel patterns and city interest points to construct urban security risk indicators. This paper combines traffic data and urban alarm data to analyze the safe travel characteristics of the urban population. The research results are helpful to explore the diversity of human group behavior, grasp the temporal and spatial laws and reveal regional security risks. It provides a reference for optimizing resource deployment and group intelligence analysis in emergency management.

Based on the dynamics index of group behavior, this paper mines the data of large shared bikes and ride-hailing in a big city of China. We integrate the urban interest points and travel dynamic characteristics, construct the urban traffic safety index based on alarm behavior and further calculate the urban safety index.

This study found significant differences in the travel power index among ride-sharing users. There is a positive correlation between user shared bike trips and the power-law bimodal phenomenon in the logarithmic coordinate system. It is closely related to the urban public security index.

Based on group-shared dynamic index integrated alarm, we innovatively constructed an urban public safety index and analyzed the correlation of travel alarm behavior. The research results fully reveal the internal mechanism of the group behavior safety index and provide a valuable supplement for the police intelligence analysis.

The purpose of this paper is to address the problem of profiling human behaviour patterns captured in surveillance videos for the application of online normal behaviour recognition and anomaly detection.

A novel framework is developed for automatic behaviour profiling and online anomaly detection without any manual labeling of the training dataset.

Experimental results demonstrate the effectiveness and robustness of the authors' approach using noisy and sparse datasets collected from one real surveillance scenario.

To discover the topics, co‐clustering topic model not only captures the correlation between words, but also models the correlations between topics. The major difference between the conventional co‐clustering algorithms and the proposed CCMT is that CCMT shows a major improvement in terms of recall, i.e. interpretability.

The diversity of social forms both regionally and historically calls for a paradigmatic reassessment of concepts used to map human societies comparatively. By differentiating “social analytics” from “explanatory narratives,” we can distinguish concept and generic model development from causal analyses of actual empirical phenomena. In so doing, we show how five heuristic models of “modes of social practices” enable such paradigmatic formation in sociology. This reinforces Max Weber’s emphasis on the irreducible historicity of explanations in the social sciences.

Explanatory narrative.

A paradigmatic consolidation of generalizing concepts, modes of social practices, ideal-type concepts, and generic models presents a range of “theoretical tools” capable of facilitating empirical analysis as flexibly as possible, rather than cramping their range with overly narrow conceptual strictures.

To render social theory as flexible for practical field research as possible.

Develops a way of synthesizing diverse theoretical and methodological approaches in a highly pragmatic fashion.

This paper aims to discuss traffic patterns generated by swarms of robots while commuting to and from a base station.

The paper adopts a mathematical evaluation and robot swarm simulation. The swarm approach is bottom‐up: designing individual agents the authors are looking for emerging group behaviour patterns. Examples of group behaviour patterns are human‐driven motorized traffic which is rigidly structured in two lanes, while army ants develop a three‐lane pattern in their traffic. The authors copy army ant characteristics onto their robots and investigate whether the three lane traffic pattern may emerge. They follow a three‐step approach. The authors first investigate the mathematics and geometry of cases occurring when applying the artificial potential field method to three “perfect” robots. Any traffic pattern (two, three or more lanes) appears to be possible. Next, they use the mathematical cases to study the impact of limited visibility by defining models of sensor designs. In the final step the authors implement ant inspired sensor models and a trail following mechanism on the robots in the swarm and explore which traffic patterns do emerge in open space as well as in bounded roads.

The study finds that traffic lanes emerge in the swarm traffic; however the number of lanes is dependent on the initial situation and environmental conditions. Intrinsically the applied robot models do not determine a specific number of traffic lanes.

The paper presents a method for studying and simulating robot swarms.

This study aims to use a narrative-based simulation approach to explore potential implications of including or excluding a dayroom in the design of an internal medicine ward.

The approach involved: collecting data in facilities using field observations and experts’ interviews; modeling representative behavior patterns in the form of rule-based narratives that direct collaborative behaviors of virtual occupants; simulating the behavior patterns in two alternative design options, one of which includes a dayroom; and analyzing the simulation results with respect to selected key performance indicators of day-to-day operations and spatial occupancy, including occupant density in corridors, number and locations of staff-visitor interactions and duration of a doctors’ round procedure.

Simulation results suggest that the presence of a dayroom reduces visitors’ density in corridors and diminishes the number of staff–visitor interactions that can delay the performing of scheduled medical procedures.

A high level of uncertainty is intrinsic to the simulation of future human behavior. Additional work is required to systematically collect large volumes of occupancy data in existing facilities, model additional narratives and develop validation protocols to assess the degree of uncertainty of the proposed model.

A limited number of studies explore how simulation can be used to study the impact of building design on operations. This study uses a narrative-based approach to address some of the limitations of existing methods, including discrete-event simulations. Preliminary results suggest that the lack of appropriate spaces for patients and visitors to socialize may cause potential disruptions to hospital operations.

The history of Organizational Development (OD) reveals a much older tradition of organizational science than the conventional wisdom would suggest. By the 1960s and 1970s OD became self‐confident and dynamic. This period was not only highly experimental but established the principles of OD for much of the twentieth century. By the end of the twentieth century new images of OD had occurred and much of the earlier thinking had been transformed. This review illustrates some examples under a series of themes that have had a major impact on the discipline of OD and on the wider thinking of organizational theorists and researchers.

Studies of public policy, particularly the explanation and prediction of policy outcomes, are motivated by a desire to improve policy success. However, most policies fall far short of solving problems. Why is it so difficult for policy to succeed? Biology's answer: because we are human. Many natural tendencies are less than optimal for the policy cognition and behavior necessary to make effective policy popular. The portions of human nature which are most interesting for our purposes include the way humans think, the role of emotion, the power of interpersonal relationships, the power of belonging to a group, and the power of competition for status. These human realities anticipate ineffective policy development. Knowing something about humans might explain why it is difficult for policy to succeed.