An Examination of How Supervisors Influence Their Subordinates to Engage in Environmental Behaviors

Employee engagement in environmental behaviors is an important topic in operations management. Drawing upon stakeholder, commitment, and organizational support theories, this study creates and tests an empirical model of how store managers (i.e., supervisors) influence their direct reports (i.e., subordinates) to become engaged in environmental behaviors. Based on a dataset derived from supervisors and their subordinates who are employed at the same grocery store location across a large retail grocery chain, we test our study's nomological model and find support for the linkages proposed. Key research and managerial implications are discussed.     

A Learning Curve Analysis of Expert System Use*

In this article, we study how an expert system affects novice problem solving in a financial risk analysis domain. We demonstrate that novice performance is improved after exposure to an expert system. Further, we show that novice performance continues to improve when the system is withdrawn. By comparing learning curves for people with exposure to those without, we can assess how much the system has benefitted its users. We demonstrate a quantitative methodology to measure the increment of learning due to the use of an information technology. We also explore the issue of how expertise is transferred from the system to the user.     

Integrating Neural Networks and Semi-Markov Processes for Automated Knowledge Acquisition: An Application to Real-time Scheduling*

Recently, artificial neural networks (ANN) have gained attention as a promising modeling tool for building intelligent systems. A number of applications have been reported in areas varying from pattern recognition to bankruptcy prediction. In this paper, we present a creative methodology that integrates computer simulation, semi-Markov optimization, and ANN techniques for automated knowledge acquisition in real-time scheduling. The integrated approach focuses on the synergy between operations research and ANN in eliciting human knowledge, filtering inconsistent data, and building competent models capable of performing at the expert level. The new approach includes three main components. First, computer simulation is used to collect expert decisions. This step allows expert knowledge to be obtained in a non-intrusive way and minimizes the difficulties involved in interviewing experts, constructing repertory grids, or using other similar structures required for manual knowledge acquisition. The data collected from computer simulation are then optimized using a semi-Markov decision model to remove data redundancies, inconsistencies, and errors. Finally, the optimized data are used to build ANN-based expert systems. The integrated approach is evaluated by comparing it with the human expert and using ANN alone in the domain of real-time scheduling. The results indicate that ANN-based systems perform worse than human experts from whom the data were collected, but the integrated approach outperforms human experts and ANN models alone.     

The Design of a Knowledge-Based Decision Support System to Support the Information Analyst in Determining Requirements

Decision support system (DSS) researchers and designers continue to look for unstructured organizational tasks where there is a critical need for intelligent computer-based support. One such decision task is information requirements determination. Requirements determination is recognized as the most crucial phase of the systems development life cycle. Unfortunately, most methodologies and CASE tools focus only on how to specify the requirements once they are determined. There is very little computer support for the process of determining requirements. This paper discusses the conceptual design and development of a knowledge-based DSS to support information analysts in the critical decision task of determining requirements for the design of effective information systems. The expert modeling support system has the expertise to assist the analyst in studying the organization as a whole and in modeling the system under study in the context of the overall organization's goals and needs. The focus of the paper is on the problems associated with building the knowledge base component of the intelligent decision support system. A prototype implementation of the system is described.     

Breastfeeding experiences and perspectives among women with postnatal depression: A qualitative evidence synthesis

BackgroundStudies show that postnatal depression affects around 10–16% of women globally. It is associated with earlier cessation of breast feeding, which can negatively impact infants’ long-term development. Mechanisms underpinning associations between mental health and women’s decision to commence and continue to breastfeed are complex and poorly understood.AimThe aim of this review was to investigate breastfeeding experiences, perspectives, and support needs of women with postnatal depression. No previous reviews were identified which had addressed this aim.MethodA systematic search was conducted of six databases to identify relevant qualitative studies. Six included studies were critically appraised and synthesised using thematic synthesis.FindingsFive themes were identified: (1) desire to breastfeed and be a ‘good mother’, (2) struggles with breastfeeding, (3) mixed experiences of support from healthcare professionals, (4) importance of practical and social support, (5) support for mental health and breastfeeding. Most women with postnatal depression expressed strong intentions to breastfeed, although some perceived ‘failure’ to breastfeed triggered their mental health problems. Practical and non-judgemental support for their mental health needs and for successful breastfeeding from healthcare professionals, family and friends are needed.ConclusionMost women with postnatal depression desired to breastfeed but experienced breastfeeding difficulties that could impact on their mental health. By offering women with postnatal depression tailored and timely support, healthcare professionals could help women minimize breastfeeding problems which could consequently impact on their mental well-being and ensure they and their infants have opportunity to benefit from the advantages that breastfeeding offers.     

The Impact of a Structured-Argument Approach on Group Problem Formulation*

Despite advances in decision analysis and decision support systems, few formulaic procedures exist for undertaking problem formulation, particularly in group settings. This leaves managers with little procedural support for the important task of carefully structuring problems. In a laboratory experiment of 29 intact student teams, we contrasted two problem formulation methodologies: a structured argument approach (based on application of formal reasoning) and a group process approach (based on private idea generation prior to public sharing and evaluation of ideas). The structured argument approach took more time to use and failed to bring about more information search and equivocality reduction in group discussions. On the positive side, however, the structured argument approach led to a greater combination of both coverage of critical issues and consensus on those issues. Use of the structured argument approach also resulted in higher satisfaction with the problem definition and commitment to implementing results of the group meeting. Overall, the results reveal cost/benefit tradeoffs associated with developing argumentation-based procedures for problem formulation.     

Cognitive Fit: A Theory-Based Analysis of the Graphs Versus Tables Literature*

A considerable amount of research has been conducted over a long period of time into the effects of graphical and tabular representations on decision-making performance. To date, however, the literature appears to have arrived at few conclusions with regard to the performance of the two representations. This paper addresses these issues by presenting a theory, based on information processing theory, to explain under what circumstances one representation outperforms the other. The fundamental aspects of the theory are: (1) although graphical and tabular representations may contain the same information, they present that information in fundamentally different ways; graphical representations emphasize spatial information, while tables emphasize symbolic information; (2) tasks can be divided into two types, spatial and symbolic, based on the type of information that facilitates their solution; (3) performance on a task will be enhanced when there is a cognitive fit (match) between the information emphasized in the representation type and that required by the task type; that is, when graphs support spatial tasks and when tables support symbolic tasks; (4) the processes or strategies problem solvers use are the crucial elements of cognitive fit since they provide the link between representation and task; the processes identified here are perceptual and analytical; (5) so long as there is a complete fit of representation, processes, and task type, each representation will lead to both quicker and more accurate problem solving. The theory is validated by its success in explaining the results of published studies that examine the performance of graphical and tabular representations in decision making.     

我国互联网扩散之地区差异的影响因素探究

基于创新扩散理论,对我国互联网扩散的地区不平衡状况及其影响因素进行了初步探索。研究采用基尼系数概念来描述互联网发展的地区不平衡,并通过回归分析探究影响互联网扩散的关键因素。研究发现,近年来我国的互联网发展的地区差距在不断缩小,其差异程度逐渐和经济发展水平的差异程度接近。而决定中国不同省份之间互联网扩散差异的主要因素是随着时间推移而有所变化的。在扩散的早期阶段,经济因素(人均GDP)具有显著影响;随着扩散过程的继续,其他因素如消费结构和生活方式也对互联网扩散有一定程度的作用。     

On a control chart for the Gini index with simulations

In this work we suggest the use of the Gini index on control charts. The asymptotic properties of Gini index are presented and the control charts based on appropriate confidence intervals are constructed. The suitability of the proposed charts are investigated by means of extensive simulations.     

地区收入、食品价格与恩格尔系数

本文以2016年我国31个省级地区截面数据为样本,构建扩展模型考察恩格尔系数与收入、食品价格之间的关系。研究发现,恩格尔系数与地区收入存在显著的负相关性,纳入食品价格后收入对恩格尔系数的影响变得更为显著,二者关系满足恩格尔定律。恩格尔系数和以地区食品价格平价代表的食品价格之间显著正相关,若再考虑其他因素,则食品价格对恩格尔系数的影响会稍有减弱。进一步将食品区分为生活必需型食品与非生活必需型食品,测算得到的基本恩格尔系数、高阶恩格尔系数与收入之间仍呈负相关关系,但与基本恩格尔系数相比,高阶恩格尔系数与收入之间的负相关性更弱。恩格尔系数受生活必需型食品价格的影响强于非生活必需型食品价格的影响,基本恩格尔系数主要受生活必需型食品价格的影响,而高阶恩格尔系数同时受到两类食品价格的影响。