What is on your mind? Using the perceptual cycle model and critical decision method to understand the decision-making process in the cockpit

Aeronautical decision-making is complex as there is not always a clear coupling between the decision made and decision outcome. As such, there is a call for process-orientated decision research in order to understand why a decision made sense at the time it was made. Schema theory explains how we interact with the world using stored mental representations and forms an integral part of the perceptual cycle model (PCM); proposed here as a way to understand the decision-making process. This paper qualitatively analyses data from the critical decision method (CDM) based on the principles of the PCM. It is demonstrated that the approach can be used to understand a decision-making process and highlights how influential schemata can be at informing decision-making. The reliability of this approach is established, the general applicability is discussed and directions for future work are considered.

Practitioner Summary: This paper introduces the PCM, and the associated schema theory, as a framework to structure and explain data collected from the CDM. The reliability of both the method and coding scheme is addressed.     

Adaptively Rational Learning

Research on adaptive rationality has focused principally on inference, judgment, and decision-making that lead to behaviors and actions. These processes typically require cognitive representations as input, and these representations must presumably be acquired via learning. Nonetheless, there has been little work on the nature of, and justification for, adaptively rational learning processes. In this paper, we argue that there are strong reasons to believe that some learning is adaptively rational in the same way as judgment and decision-making. Indeed, overall adaptive rationality can only properly be assessed for pairs of learning and decision processes. We thus present a formal framework for modeling such pairs of cognitive processes, and thereby assessing their adaptive rationality relative to the environment and the agent’s goals. We then use this high-level formal framework on specific cases by (a) demonstrating how natural formal constraints on decision-making can lead to substantive predictions about adaptively rational learning and representation; and (b) characterizing adaptively rational learning for fast-and-frugal one-reason decision-making.     

From BPMN process models to DMN decision models

The interplay between process and decision models plays a crucial role in business process management, as decisions may be based on running processes and affect process outcomes. Often process models include decisions that are encoded through process control flow structures and data flow elements, thus reducing process model maintainability. The Decision Model and Notation (DMN) was proposed to achieve separation of concerns and to possibly complement the Business Process Model and Notation (BPMN) for designing decisions related to process models. Nevertheless, deriving decision models from process models remains challenging, especially when the same data underlie both process and decision models. In this paper, we explore how and to which extent the data modeled in BPMN processes and used for decision-making may be represented in the corresponding DMN decision models. To this end, we identify a set of patterns that capture possible representations of data in BPMN processes and that can be used to guide the derivation of decision models related to existing process models. Throughout the paper we refer to real-world healthcare processes to show the applicability of the proposed approach.     

Integrating a Decision Tree Perspective at the Operational-Level of BPM+

Decision trees are among the best-known decision-making techniques and have been used extensively for both data analysis and predictive modeling. BPM+ is a novel process modeling approach that helps represent business process models in a consistent and structured way to meet different stakeholders’ process representation needs. This paper reports on the outcomes of an ontological analysis of the potential use of decision-tree representations as a new BPM+ perspective for the operational level of abstraction. This new perspective effectively demonstrates how a specialized/operational BPM stakeholder perspective can be used to improve the existing organizational business process model repository.     

The contribution of social network sites to exposure to political difference: The relationships among SNSs, online political messaging, and exposure to cross-cutting perspectives

The increasing popularity of social network sites (SNSs) has raised questions about the role of social network media in the democratic process. This study explores how use of SNSs influences individuals’ exposure to political difference. The findings show a positive and significant relationship between SNSs and exposure to challenging viewpoints, supporting the idea that SNSs contribute to individuals’ exposure to cross-cutting political points of view. Partisanship was not found to interact with SNS use, suggesting that SNSs contribute to expanding exposure to dissimilar political views across individuals’ partisanship. Online political messaging also has a direct effect on exposure to dissimilar viewpoints, and it mediates the association between SNSs and exposure to cross-cutting political views.     

智能需求获取与建模研究综述

需求获取和建模是指从需求文本或记录中获取显式和隐式的需求,并通过表格化、图形化、形式化等方法构建相应模型的过程,是软件开发过程中极为关键的一步,为后续系统设计与实现铺平道路,提高软件开发效率和质量,提升软件系统稳定性和可行性.研究者们在需求获取与建模方面获得了一系列研究成果,根据其关注阶段不同,可以将它们分为需求知识提...     

Social fMRI: Investigating and shaping social mechanisms in the real world

We introduce the Friends and Family study, a longitudinal living laboratory in a residential community. In this study, we employ a ubiquitous computing approach, Social Functional Mechanism-design and Relationship Imaging, or Social fMRI, that combines extremely rich data collection with the ability to conduct targeted experimental interventions with study populations. We present our mobile-phone-based social and behavioral sensing system, deployed in the wild for over 15 months. Finally, we present three investigations performed during the study, looking into the connection between individuals’ social behavior and their financial status, network effects in decision making, and a novel intervention aimed at increasing physical activity in the subject population. Results demonstrate the value of social factors for choice, motivation, and adherence, and enable quantifying the contribution of different incentive mechanisms.     

Identifying competences for the design of systems supporting complex decision-making tasks: a managerial planning application

The work presented in this paper is addressed to the front-end phases of the development of a system supporting a complex decision-making task: high-level managerial planning in small-to-medium enterprises (SMEs). It attempts to identify characteristics of the competences possessed by experienced managers and used when taking high-level managerial planning decisions, and to assess their potential implications for system design. The work is based on the assumption that the design of effective systems supporting complex decision-making tasks in a specific domain, would require elicitation of competences possessed by experienced persons in the domain, especially those related to the mental processes followed when confronting the cognitive constraints involved in the specific decision-making environment. Such an investigation would lead to the development of systems improving decision making since they would (1) respond to the difficulties met by potential users in performing complex decision-making tasks; (2) reduce possible negative consequences of users' decision-making competences; and (3) at the same time they would achieve the required compatibility with users' mental processes. The research methodology was based on a planning scenario and on an analysis of verbal protocols obtained from a sample of small-enterprise managers confronted with this scenario. Results provide evidence about (1) the type of decisions and actions taken by experienced managers when confronted with the cognitive constraints involved in managerial planning situations; (2) phases and sequence of the process of arriving at planning decisions; and (3) data used and types of analyses performed. Some general implications are drawn from these results with respect to the configuration of a system aiming at supporting managerial planning. These refer to the type of support to be provided at various phases of the planning process, possible features of the human-computer interface, and generic or task/user specific aspects of the system.     

基于感知效用模型的“均值偏向”形成机理

在经典报童模型的基础上引入概率选择理论,发现决策者对需求发生的感知概率不符合贝叶斯公理,而为截尾正态分布。鉴于此,提出一种感知效用下的最优库存策略,并采用行为实验的方法测算出不同产品的决策噪音;根据行为实验的决策数据,仿真模拟了不同成本产品中决策者的订购行为。结果显示：感知效用模型可以解释库存决策中的“均值偏向”现象;当产品生产成本??逐渐接近(??+??)/2时,“均值偏向”现象将逐渐消失;随着??的增大,单位均值偏向度将不断减小。由此可见,“均值偏向”现象不是一种普遍现象,仅存在于部分产品的订购行为中。     

Application of MADM in a fuzzy environment for selecting the best barrier for offshore wells

A fuzzy Multi Attribute Decision Making (FMADM) method, which is suitable for treating group decision making problems in a fuzzy environment, is proposed for ranking offshore well barriers from a cost-benefit view point. It is obvious that much knowledge in the real world is fuzzy rather than precise. MADM decision data is usually fuzzy, crisp, or a combination of the two. A useful model is proposed here in order to handle both fuzzy and crisp data. Imprecision and ambiguity in the calculation of a performance rating are incorporated into MADM whereby fuzzy set theory provides a mathematical framework for modeling them. Human opinions often conflict in group decision-making. The purpose of fuzzy MADM is to aggregate the conflicting opinions. In general, one expert’s opinion for a given attribute may be different from others’. Therefore, it is necessary to develop an appropriate method of aggregating multiple experts’ opinions, taking into account a degree of importance of each expert in the aggregation procedure. The weights of all attributes and experts are estimated using a Fuzzy Analytical Hierarchy Process (FAHP). Finally, the best well barrier or risk control option (RCO) with respect to cost and benefit is selected using a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method.     

Decision support for moving from a single product to a product portfolio in evolving software systems

Successful software systems continuously evolve to accommodate ever-changing needs of customers. Accommodating the feature requests of all the customers in a single product increases the risks and costs of software maintenance. A possible approach to mitigate these risks is to transition the evolving software system (ESS) from a single system to a portfolio of related product variants, each addressing a specific customers’ segment. This evolution should be conducted such that the extent of modifications required in ESS's structure is reduced. The proposed method COPE+ uses preferences of customers on product features to generate multiple product portfolios each containing one product variant per segment of customers. Recommendations are given to the decision maker to update the product portfolios based on structural analysis of ESS. Product portfolios are compared with the ESS using statechart representations to identify the level of similarity in their behaviors. A proof of concept is presented by application to an open-source text editing system. Structural and behavioral analysis of candidate portfolios helped the decision maker to select one portfolio out of three candidates.     

Stochastic programming and scenario generation within a simulation framework: An information systems perspective

Stochastic programming brings together models of optimum resource allocation and models of randomness to create a robust decision-making framework. The models of randomness with their finite, discrete realisations are called scenario generators. In this paper, we investigate the role of such a tool within the context of a combined information and decision support system. We explain how two well-developed modelling paradigms, decision models and simulation models can be combined to create “business analytics” which is based on ex-ante decision and ex-post evaluation. We also examine how these models can be integrated with data marts of analytic organisational data and decision data. Recent developments in on-line analytical processing (OLAP) tools and multidimensional data viewing are taken into consideration. We finally introduce illustrative examples of optimisation, simulation models and results analysis to explain our multifaceted view of modelling. In this paper, our main objective is to explain to the information systems (IS) community how advanced models and their software realisations can be integrated with advanced IS and DSS tools.     

A participative end-user method for multi-perspective business process elicitation and improvement

A business process can be characterized by multiple perspectives (intentional, organizational, operational, functional, interactional, informational, etc). Business process modeling must allow different stakeholders to analyze and represent process models according to these different perspectives. This representation is traditionally built using classical data acquisition methods together with a process representation language such as BPMN or UML. These techniques and specialized languages can easily become hard, complex and time consuming. In this paper, we propose ISEA, a participative end-user modeling approach that allows the stakeholders in a business process to collaborate together in a simple way to communicate and improve the business process elicitation in an accurate and understandable manner. Our approach covers the organizational perspective of business processes, exploits the information compiled during the elicitation of the organizational perspective and touches lightly an interactional perspective allowing users to create customized interface sketches to test the user interface navigability and the coherence within the processes. Thus, ISEA can be seen as a participative end-user modeling approach for business process elicitation and improvement.     

Exploring factors influencing consumers’ behavioral intention to adopt broadband in Malaysia

The purpose of this paper is to examine various normative, attitudinal and control factors influencing consumers’ intention to adopt broadband internet in a developing country such as Malaysia. This study is based on empirical data collected using a self-administered questionnaire relating to the normative, attitudinal and control variables. Structural equation modeling analysis is conducted to test the role of numerous variables on consumers’ behavioral intentions to adopt broadband internet in Malaysia. Results revealed that Primary Influences (PI), Relative Advantage (RA), Hedonic Outcomes (HO), Facilitating Conditions Resources (FCR), and Self-Efficacy (SE) are positively associated with consumers’ Behavioral Intention (BI) to adopt broadband in Malaysia. The significance of this research study is twofold. Practically, this research study provide some useful guidelines to industry players, be it the internet service providers (ISPs) or the policy makers, to understand which are the factors (primary influences, self-efficacy, relative advantage, hedonic outcomes and facilitating conditions resources) that can have an influence on consumers’ intention to adopt broadband technology. It was found that primary influences, self-efficacy and relative advantage are the key determinants that influences consumers’ broadband adoption. From here, practitioners could take into consideration our findings when revising and restructuring their marketing strategy. Theoretically, the research framework used in this study is an extension from the past research models used (i.e. TPB, DOI and MATH). With the newly integrated framework, a greater level of comprehension can be attained with regards to the broadband acceptance among the Malaysian consumers.     

Extension of the VIKOR method for group decision making with extended hesitant fuzzy linguistic information

Group decision-making approaches are very important due to the complexity and uncertainty of many real-world decision-making problems. Some of the decision-making problems are defined in qualitative frameworks. Extended hesitant fuzzy linguistic term set (EHFLTS) is proposed as a new and powerful tool for elicitation of hesitant qualitative information in group decision-making process. In this paper, we first introduced the comparison laws and a family of distance and similarity measures for extended hesitant fuzzy linguistic terms (EHFLTs) and EHFLTSs, respectively. Next, we developed the extended hesitant fuzzy linguistic (EHFL)-VIKOR method as a qualitative multi-attributes group decision-making approach based on the EHFLTS distance measures to deal with the qualitative hesitancy in group decision making. Finally, we presented an application example about selection of suitable telecommunications service provider of small- and medium-sized enterprises to verify applicability and validation of proposed method in the process of qualitative group decision making.

     

Tobit model with covariate dependent thresholds

Tobit models are extended to allow threshold values which depend on individuals’ characteristics. In such models, the parameters are subject to as many inequality constraints as the number of observations, and the maximum likelihood estimation which requires the numerical maximisation of the likelihood is often difficult to be implemented. Using a Bayesian approach, a Gibbs sampler algorithm is proposed and, further, the convergence to the posterior distribution is accelerated by introducing an additional scale transformation step. The procedure is illustrated using the simulated data, wage data and prime rate changes’ data.     

Ensuring the quality of conceptual representations

High quality data and process representations are critical to the success of system development efforts. Despite this importance, quantitative methods for evaluating the quality of a representation are virtually nonexistent. This is a major shortcoming. However, there is another approach. Instead of evaluating the quality of the final representation, the representation process itself can be evaluated. This paper views the modeling process as a communication channel. In a good communication channel, sufficient error prevention, error detection, and error correction mechanisms exist to ensure that the output message matches the input message. A good modeling process will also have mechanisms for preventing, detecting, and correcting errors at each step from observation to elicitation to analysis to final representation. This paper describes a theoretically-based set of best practices for ensuring that each step of the process is performed correctly, followed by a proof of concept experiment demonstrating the utility of the method for producing a representation that closely reflects the real world.     

An integral approach to free-form object modeling

Presents an approach to free-form object modeling from multiple range images. In most conventional approaches, successive views are registered sequentially. In contrast to the sequential approaches, we propose an integral approach which reconstructs statistically optimal object models by simultaneously aggregating all data from multiple views into a weighted least-squares (WLS) formulation. The integral approach has two components. First, a global resampling algorithm constructs partial representations of the object from individual views, so that correspondence can be established among different views. Second, a weighted least-squares algorithm integrates resampled partial representations of multiple views, using the techniques of principal component analysis with missing data (PCAMD). Experiments show that our approach is robust against noise and mismatch     

陆军合同作战指挥决策过程建模

现代作战的快速性,使得指挥员完成决策任务必须依赖于计算机辅助决策的帮助,而开发实用的决策支持系统需要有决策过程模型作为基础.针对目前这类过程模型存在的不足,根据陆军合同作战指挥的特点,通过将决策者和辅助决策者以及计算机应用程序功能综合纳入建模过程,提出了"一条主线、两层分级、三种关系,四种活动"为要素的主从式建模方法,其特点是便于决策者、辅助决策者以及参与决策者等相关人员的相互了解和沟通,突出了计算机应用程序在模型中应具有的基本功能,在辅助决策系统的分析设计上,为军事和技术人员提供了一种便于交互和便于理解的表示方式.     

Internet anxiety: An empirical study of the effects of personality,beliefs, and social support

We examined sources of Internet anxiety; specifically modeling the ties from broad dispositional traits (computer anxiety, computer self-efficacy, and personal innovativeness with IT), beliefs about the work environment (about the adequacy of resources and trust in technology), and two forms of social support for IT (leader and peer support) to individuals’ anxiety about using Internet applications. We tested our model using respondents who participated in virtual teams during a 16-week period. Our findings suggested that Internet anxiety was affected both by the users’ personality and by beliefs that can be influenced by providing adequate resources to support the technology, encourage trust in technology, and working to assure users that leaders and peers are supportive of their using the technology. Our findings suggest that by providing appropriate resources and fostering a supportive environment, leaders could reduce Internet anxiety and thus influence the use of technology in the workplace in ways that benefit organizations.