Assessing the reversal of investor sentiment

Assessing the reversal of sentiment in stock markets is needed because, according to the social mood cycle, the change of social mood over time is an antecedent of price movements. The purpose of this study is to empirically assess reversal of investor sentiment, to show the phases of social mood cycle from increasing mood to decreasing mood, and to explain the dynamic change in market inefficiency from increasing to decreasing. Growth modeling, developed particularly for dealing with the change over time, is used in this study for assessing the reversal of investor sentiment. The autocovariance structure of errors and the variances/covariances of the random coefficients are all taken into account in the model. The results have indicated that the change in investor sentiment over time is inverted U-shaped for the entire market. Moreover, arbitrage constraint and stock characteristics exert a joint moderating effect on sentiment reversal. Less arbitrage constraint can strengthen sentiment reversal only when the market for individual stocks is dominated by noise traders. Based on the results obtained, we discuss asset pricing, liquidity management, and market intervention.     

Longitudinal analysis versus cross-sectional analysis in assessing the factors influencing shoppers’ impulse purchase behavior – Do the store ambience and salesperson interactions really matter?

Numerous studies in the marketing literature focused on consumer behavior in general, but relatively few studies have examined Impulse purchase behavior (IPB). Although few studies examined IPB, the vast majority of the studies were conducted using the cross-sectional design. These studies suffer from certain limitations like random measurement error, common method bias, causality & validity-related issues that are inherently associated with the cross-sectional design. Despite these limitations, very few studies have examined the IPB using the longitudinal design. Multilevel structural equation modeling (ML-SEM) is conducted in the study to analyze the longitudinal data for examining the changes in the causal effects of the factors influencing the shoppers' IPB over a period of time. Additionally, structural equation modeling (SEM) is conducted to examine changes in the causal effects of the factors influencing IPB at each time point of data collection. Drawing upon the stern's model and stimulus-organism-response model, the study examines the causal effects of the factors influencing the IPB. The results of ML-SEM indicate significant fluctuations in the factors influencing IPB over time. Similarly, the results of SEM indicates that few factors (like store ambience and salesperson interactions) have shown a significant influence on IPB in the initial time points (i.e., during the initial store visits of shoppers), but became insignificant over a period of time in their subsequent store visits. The findings suggest that the store crowd, secondary customers influence, and in-store promotions show a significant influence on the IPB, compared to the store ambience and salesperson interactions.     

A cellular automata-based land-use model as an integrated spatial decision support system for urban planning in developing cities: The case of the Bogotá region

Bogotá and the 17 neighboring municipalities make up one of the biggest metropolitan areas in Latin America. However, despite strong functional interactions within the area, there is no official government body at this level in charge of coordinating authorities and providing solutions to the wide variety of issues arising in the regional urban land system. Aiming at providing an insight on future land-use developments linked to new transport infrastructures and at offering a tool to support territorial decision-making, this paper presents a cellular automata-based (CA) model based in Metronamica® software, that allows testing different scenarios based on potential land-use policies, environmental suitability and transport alternatives.There has not been, so far, an urban planning tool that accounts for the complexities of this region. CA-based land-use simulations constitute a useful approach to understanding the impacts of urban planning policies and regulations. This tool can help to improve inter-territorial and inter-institutional coordination, which through planning and management policies seek a spatially integrated development, with a long-term perspective.The CA-based model proposed was calibrated to reproduce land-use changes between 2007 and 2016 using different methods and indicators. The model was used to simulate and analyze eight scenarios with different policy directions of transport infrastructure in the future of the region. The results of the simulations reflect the dynamics of territorial occupation. The calibration indices in the experiment indicate a high degree of suitability for the CA Bogotá model, proving its effectiveness and potential as a useful tool for decision-making. The results show that occupation scenarios with restricted developable zones within the city, tend to have the greater dispersion rate in the study area, compared to scenarios where land development plans are promoted in Bogotá, which representing a more compact development.     

Incorporating textual information in customer churn prediction models based on a convolutional neural network

This study investigates the value added by incorporating textual data into customer churn prediction (CCP) models. It extends the previous literature by benchmarking convolutional neural networks (CNNs) against current best practices for analyzing textual data in CCP, and, using real life data from a European financial services provider, validates a framework that explains how textual data can be incorporated in a predictive model. First, the results confirm previous research showing that the inclusion of textual data in a CCP model improves its predictive performance. Second, CNNs outperform current best practices for text mining in CCP. Third, textual data are an important source of data for CCP, but unstructured textual data alone cannot create churn prediction models that are competitive with models that use traditional structured data. A calculation of the additional profit obtained from a customer retention campaign through the inclusion of textual information can be used by practitioners directly to help them make more informed decisions on whether to invest in text mining.     

Partial least squares structural equation modeling in HRM research

Abstract

Partial least squares structural equation modeling (PLS-SEM) has become a key multivariate analysis technique that human resource management (HRM) researchers frequently use. While most disciplines undertake regular critical reflections on the use of important methods to ensure rigorous research and publication practices, the use of PLS-SEM in HRM has not been analyzed so far. To address this gap in HRM literature, this paper presents a critical review of PLS-SEM use in 77 HRM studies published over a 30-year period in leading journals. By contrasting the review results with state-of-the-art guidelines for use of the method, we identify several areas that offer room of improvement when applying PLS-SEM in HRM studies. Our findings offer important guidance for future use of the PLS-SEM method in HRM and related fields.     

农产品供应链重构风险传导SIR建模与仿真研究

[目的]利用动力学SIR模型模拟农产品供应链重构内生风险传导过程,以期在有效把握核心重构风险传导规律基础上为整体管控重构进程风险提出前瞻性思路。[方法]基于农产品供应链重构风险整体构架和重构进程风险传导复杂网络,以湖北省243家大型连锁超市生鲜农产品供应链2007—2017年重构样本数据为研究对象,建立重构进程内生风险传导SIR模型和规划演化模式,利用Matlab软件对模型仿真得到有效管控状态下演化趋势。[结果]在以战术性重构为主导组织结构战略性重构中进程风险传导安全边际X1s超过50%,决定了其净风险阈α0(i)、β0(i),相应的业务单元和功能模块重构进程风险预警和风险恢复能力提高值是主控指标,对进程风险传导感染率x1(i)和恢复率x2(i)起主导作用。[结论]近年来土地流转驱动农产品供应链重构中组织结构重构整体具有战略性,在以战术性重构为主导风险传导管控中重点应加强业务单元和功能模块重构进程在重构易感状态(S)、感染传播状态(I)管控能力,能有效降低波动幅度。     

Synchronizing relational benefits with customer commitment profiles

ABSTRACT

The literature no longer considers commitment to be a distinct variable. Instead, commitment represents a combination of affective, calculative, and normative dimensions for individual customers, resulting in the adoption of a person-centric view for its measurement. However, customer satisfaction as a result of confidence benefit, social benefit, and special treatment benefit may vary among customers with different commitment profiles which encourages variable-centric view. Considering both variable- and person-centric views, this study uses survey data to examine the impact of relational benefits on the satisfaction of customers with different commitment profiles. It also examines the moderation role of relationship age. With cluster analysis identifying three commitment profiles, findings from structural equation modeling confirmed that highly-committed customers expected excessive special treatment benefit; low-commitment customers preferred confidence benefit to reduce cognitive dissonance; while affective-dominance customers expected all three types of benefit proportionately. The study’s theoretical and practical contributions conclude the paper.     

数字地面模型新进展：TIN2.0、3D表面 塑型线和自由形态建模工具

竖向设计是人类在景观中进行的基本活动。人类对 室外空间的任何干预都涉及对地表形态的设计。在过去的几十 年中，数字设计的发展不仅改变了表现的方法，而且改变了设 计的过程。就地形建模而言，该技术实现了三维可视化和任务 自动化，例如土方计算和自动产生横截面。但在重点考察最新 的建筑信息模型(BIM)如何应用和实施这项技术时，不难发现 地形建模过程并没有充分利用技术带来的潜在优势。实际上， 三维建模工具、基于组件的建模和分析、设计验证，以及协同 设计是可以集成到数字地面模型中的。识别了现有数字建模解 决方案中的主要缺陷并为其进一步发展提供机会，提出了一 项整合性的数字地面模型建模过程，该过程引入了TIN2.0曲 面，对现有的TIN曲面进行了升级，允许在同一曲面中同时存 在规则三角网和不规则三角网，并开发了一套基于三维线和自 由形态设计工具的建模工具，推动风景园林信息模型框架的发 展以满足风景园林师及其他专业人士，如建筑师和土木工程师 进行地形建模的需求。通过案例研究对提出的建模过程进行了 测试和验证。结果表明，生成的数字曲面具有较高精度，可以 具象地表现地形，允许设计过程在三维线或自由形态设计工具 的基础上进行。所有地形建模均在三维数字模型上进行     

Assessment of Consumer Behavior Towards Environmental Responsibility: A Structural Equations Modeling Approach

This paper analyses the factors impacting consumer environmental responsibility using a structural equation modeling approach. Consumer environmental responsibility is the intention of a person to act towards remediation of environmental problems not as an individual user with economic interests but as a responsible citizen having concerns about the social and environmental wellbeing of society. Therefore, awareness of environmental problems and knowledge of remedial alternatives will help individuals to pursue their chosen action and bolster a genuine desire to act and determine the measures for alleviation of environmental challenges. The four dimensions of an environmentally responsible consumer – opinion and beliefs, willingness, awareness, and an ability to act – are analysed. During the analysis, the dimension of ‘ability to move’ is found to be critical, because it has a direct influence on the capacity of the consumer to act. This research is intended to guide policy‐ and decision‐makers of regulatory bodies in understanding consumer behavior towards improving environmental performance index. It also helps organizational managers to make their supply chains green, and competitive, which in turn improves brand image and overall organizational performance. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment