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Previous literature has compared the effectiveness of different styles of leadership, yet most of this research has not compared different levels of analyses regarding leader styles or behaviors. This shortcoming often limits our understanding of how leadership acts on a phenomenon of interest to a single level of analysis. This article develops a computational model and describes a levels-based comparison of four types of leadership that represent three different levels: individual, dyad, and group. When examined across a dynamic group decision-making optimization scenario, group-based leadership is found to produce decisions that are closer to optimal than dyadic-based and individual-based leadership. An alternative computational model varying individual cognitive and experience-based components among group members also indicates that group-based leadership produces more optimal decisions. First published in Leadership Quarterly (Dionne, S. D., & Dionne, P. J. (2008). Levels-based leadership and hierarchical group decision optimization: A simulation. Leadership Quarterly, 19, 212–234), this version offers an updated introduction discussing simulation as a theoretical development tool and supplies additional evidence regarding the growth of simulation methods in leadership research.

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

Distributed performance arrangements are increasingly used by organizations to structure dyadic and team interactions. Unfortunately, distributed teams are no panacea. This chapter reviews some of the advantages and disadvantages associated with the geographical and temporal distribution of team members. An extended discussion of the implications of distributed team performance for individual, team, and organizational decision making is provided, with particular attention paid to selected cultural factors. Best practices and key points are advanced for those stakeholders charged with offsetting the performance decrements in decision making that can result from distribution and culture.

Purpose – The aim of this study is to determine the impact of feeling bored on managers' decision-making in the digital age under conditions of increased uncertainty by examining the role of personality trait openness and empirically testing such relationships within the context of retail middle managers.

Design/methodology/approach – Feeling bored was defined within a broader Decision-Making Process Model, which included the personality trait openness. An empirical study with retail middle managers was conducted to examine the relationships between feeling bored and decision-making competence (DMC). Regression models were fit to test whether feeling bored affects DMC and whether the associations were moderated by personality trait openness.

Findings – In the relationship between feeling bored and DMC, the moderating role of the personality trait openness was established. Results showed that feeling bored has a significant negative association with middle managers' confidence levels and risk perceptions when making decisions. Results also provided evidence that the learning component of personality trait openness plays a moderating role in the relationship between feeling bored and DMC. Most notably, the learning component of personality trait openness neutralizes the negative effects of feeling bored on managers' ability to remain appropriately confident when making decisions. In addition, the learning and inquisitive components temper the positive association between mood excited and risk perceptions. Limitations to the study are outlined.

Practical implications – Since trait openness (specifically its learning component) benefits decision-making contexts, it makes trait openness a worthy criterion to include when screening aspirant retail middle managers. The benefits of trait openness (specifically its learning component) for middle managers and their teams (especially when they are feeling bored) are indicated, since learning neutralizes the negative effect feeling bored has on appropriate confidence levels in retail management decision-making contexts.

Social environments can be presented as complex systems that are continually changing their structures in a nonlinear fashion. However, this notion of complexity is commonly disregarded in the study of strategic interactions between competing actors. One of the major reasons for this is the inability to collect sufficient empirical data in order to adequately study decision making under dynamic circumstances. In order to cope with this problem an online simulator module is being developed. This module allows researchers to create interactive simulators that confront human subjects with virtual social environments designed by the researcher. Unlike previous simulator modules, this one provides a high degree of flexibility and imposes fewer restrictions on the simulated environment and the manner in which decisions can be made. Thus, the subjects operating this simulator can pursue multiple policies simultaneously rather than choosing between alternatives. They can make decisions in real time and receive feedbacks also at anytime, including delayed feedbacks. Decisions that are made can alter the environment, resulting in changing payoffs and the policies that are available. It is also possible to provide subjects operating the simulator with different formats for presenting information. Another significant feature is the capability to monitor when choices are made and what information is being analyzed and when it is being observed. In comparison to other simulator modules that have been developed in the past, this one is not based on an old simulation language but is completely newly programmed in a language designed for online interactions.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

This chapter explores Prospect Theory — a descriptive model of modelling individual choice making under risk and uncertainty, and its applications to a range of travel behaviour contexts.

The chapter provides background on Prospect Theory, its basic assumptions and formulations, and summarises some of its theoretical developments, applications and evidence in the field of transport research.

A body of empirical evidence has accumulated showing that the principle of maximisation of expected utility provides limited explanation of travel choices under risk and uncertainty. Prospect Theory can be seen as an alternative and promising framework for travel choice modelling (although not without theoretical and practical controversy). These findings are supported by empirical observations reported in the literature reviewed in this chapter.

The chapter provides a detailed account of the design and results of accumulated research in travel behaviour research that is based on Prospect Theory’s observations, insights and formulations. The potential of Prospect Theory for particular decision-making in travel behaviour research is articulated, main findings are presented and discussed, and limitations are identified, leading to further research needs.

This article reviews the quantitative marketing literature on artificial intelligence (AI) through an economics lens. We apply the framework in Prediction Machines: The Simple Economics of Artificial Intelligence to systematically categorize 96 research papers on AI in marketing academia into five levels of impact, which are prediction, decision, tool, strategy, and society. For each paper, we further identify each individual component of a task, the research question, the AI model used, and the broad decision type. Overall, we find there are fewer marketing papers focusing on strategy and society, and accordingly, we discuss future research opportunities in those areas.

This paper suggests that firm strategic capabilities are developed through accumulated learning and associated investment processes and that it is these learning processes, and the resource investments that follow from decisions about them, rather than the activities or resources of the firm per se, that provide a basis of sustainable competitive advantage. Specifically, we suggest that gathering information about customer behavior, the managerial perceptions that come from learning about customer behavior, and the investment decisions that follow from those perceptions provide the basis for the development, or for the failure to develop, of firm capabilities. We further argue that such learning processes will differ with market environments, and that firm performance will reflect such learning processes actually develop in different market environments.