The Non‐Observed Economy in Portugal: The monetary model and the MIMIC model

This paper offers estimations for the Portuguese path of the Non‐Observed Economy (NOE), in the period 1970–2015, through two seminal approaches: monetary method and the Multiple Indicators Multiple Causes (MIMIC) model. It is observed that the tax burden and social benefits are its main causes. Then, to get a more in‐depth understanding of the phenomenon, it provides a study of the Granger causality between the NOE and the official Gross Domestic Product (GDP), emphasizing the implications of the NOE on the Portuguese economy. Evidence has been found for the existence of bidirectional causality between the NOE and the GDP, suggesting that the formal economy affects the NOE, and conversely that the NOE affects the economic growth.     

From disruptively digital to proudly analog: A holistic typology of digital transformation strategies

Recently booming academic interest in digital transformation aims to provide continuous support to managers in dealing with this important issue. However, as with all new fields, the scholarly literature is characterized by increased variability and diversity of topics covered, constructs used, and the relationships between them, resulting in an unclear and blurry understanding of the whole of digital transformation. Our article closes this gap by identifying distinctive digital transformation strategies in terms of two critical dimensions: usage of digital technologies and readiness of a business model for digital operation. The result is a typology of four generic digital transformation strategies that essentially differ in the primary motivation and target of transformation, leadership style, importance of skills like creativity and entrepreneurial spirit among employees, risks and challenges faced in the process, consequences of potential failure, and available tactics for improvement. By providing heuristics and a systematic basis for comparison of different strategies, it is our belief that the proposed framework will be useful to researchers and managers responsible for and interested in digital transformation.     

黔东南山地生态农业发展评价及预测研究

[目的]对2012~2016年黔东南州山地生态农业发展做出评价,并预测其2018~2027年的发展情况,以期了解黔东南地区农业可持续发展能力及未来趋势的变化规律。[方法]以黔东南及贵州《2013~2017年统计年鉴》为数据来源,通过构建评价指标体系,利用层次分析法及加权评分法对2012~2016年山地生态农业发展做出评价;并运用灰色模型,借助Matlab工具,对黔东南山地生态农业发展做出预测。[结果]2010~2016年黔东南州山地生态农业的经济、生态、社会效益处于发展上升阶段,协调度良好,但生态效益发展最低,其中2015年经济、社会、生态系统可持续发展良好,但由于持续保护,2016年出现生态保护过度,经济和综合效益下降现象,因此发展模式有待于向发展经济和社会效益方面倾斜;黔东南州山地生态农业在2018~2027年将会处于发展上升阶段,但其发展缓慢,仍存在一定限制因素。[结论]政府应积极调整农业产业结构,转变农业发展思路,可将部分生态农业与旅游相结合,发挥区位特色的同时,提升品牌的知名度。加大力度引导农业园区和重点产业的发展,推进农业农村改革试点的运行,加大新型农人的培育,促进高效、现代、特色生态农业的发展。     

河南省城镇化时空格局及驱动力分析

[目的]通过分析城镇化时空格局及其驱动力用来表现河南省城镇化近10年状态,并通过驱动力分析其主要影响因素。[方法]文章选取人均GDP、财政收入、第三产业生产总值、全社会固定资产投资、在岗职工平均工资、各市参加医疗保险人口、天然气用气人口、各市普通高中毕业生、废水排放量、生活垃圾处理量、固体废物处理量、道路清扫保洁面积等12个指标构建综合指标体系,运用SPSS因子分析确定权重,测算2005~2015年河南省城镇化发展水平并分析其时空演变特征,在此基础上利用灰色关联度分析城镇化发展驱动力。[结果]河南省城镇化水平在时间维度上呈上升趋势,空间上表现为高城镇化水平集中在河南省西北部地区,有向东北部发展的趋势;低水平城镇化地区集中在河南省中南部地区且数量逐渐减少;中等水平的城镇化地区集中在河南省周边的地级市,数量逐渐增多,且有向高等城镇化水平发展的趋势;就驱动力影响力而言,市场机制高居第一,其次是政府作用、自身发展、外商投资。[结论]河南省城镇化水平空间差异显著,并受多种驱动力共同影响。     

一种级联两箱通用数字预失真器及其辨识算法

提出了一种由单形规范线性分段(SCPWL)函数与记忆多项式级联的数字预失真器，并给出了复数域两步最小二乘参数辨识算法。不同于以往一种预失真器适用一种功放模型的情况，所提的预失真算法利用SCPWL函数的分段特性以及记忆多项式的非线性记忆特性，在完成参数辨识的同时自动地调整结构，可适用于传统以及强非线性新型功放模型的线性化补偿。将所提预失真器分别应用于传统记忆多项式、两箱模型以及新型包络跟踪功放。经过计算机仿真，功放输出的幅频特性和频谱曲线表明所提预失真器能够有效地补偿多种功放的非线性特性。算法仿真比较结果也表明，针对包络跟踪功放，所提复数两步最小二乘算法的邻道泄漏比(ACLR)可改善约35 dB，性能优于最小均方(LMS)类算法约30 dB。     

基于经济新常态的长春市水资源开发利用潜力评价

以长春市为研究对象,基于未来经济处于新常态的发展态势,构建包含水资源、社会、经济、生态环境4个子系统的评价指标体系,并确定各指标的评价等级标准;基于模糊数学理论以及层次分析法构建包括目标层、准则层、指标层的3层模糊综合评价模型,以2015年为现状水平年,应用模型对长春市水资源开发利用潜力进行综合评价。结果表明:长春市水资源开发利用程度处于中等偏上水平,各辖区水资源开发利用规模不平衡,可通过产业结构调整提高全市用水效率,为经济持续增长提供保障。     

海南城乡居民消费水平差异性分析和预测

从1985-2018年海南城乡居民收入、消费数据出发，分别建立消费关于收入、消费差距关于收入差距的自回归模型，结果表明农村居民当期消费更易受近期收入和消费水平的影响，具有不稳定性。再利用GM(1,1)模型预测城乡居民收入差距，结合自回归模型，完成未来10年海南城乡消费差距的预测：收入差距和消费差距将呈直线递增趋势，收入差距的增幅高于消费差距增幅。缩小海南城乡居民消费差距的根本途径在于缩小收入差距，应因地制宜，切实提高农民收入水平。     

Investment decision-making under economic policy uncertainty

It is widely established that economic policy uncertainty (EPU) affects investment decisions and performance, yet research in this area has overlooked the direct property investment market. This article seeks to rectify this and proposes a multistage multilevel analytical framework to offer new insights and a richness of findings. Using a news-based measure of EPU in the United Kingdom, and controlling for economic conditions, a national-level analysis reveals some evidence of Granger-Causality between EPU and total returns, indicating that pricing is responsive to uncertainty. These findings suggest that EPU is an important risk factor for direct property investments, with pricing implications. Differences in data and performance measure are important, however, with income returns unresponsive. A micro-level investigation begins to reveal some of the asset-pricing decisions underpinning the national results, indicating investors’ concerns for income streams are consistently high, regardless of varying EPU. Pricing can also cause changes in EPU, such as in the retail and industrial markets (increasingly linked through logistics) reflecting sector-specific stakeholder groups and newsworthy issues. This evidence highlights how important it is for policy-makers to understand the complex and bi-directional relationship, that indecision can undermine investment confidence and cause investment market volatility, in turn raising EPU.     

Green human resource management: Development of a valid measurement scale

The objective of the study was to develop a valid measurement scale for green human resource management (HRM). Even though the common practices of green HRM have been presented in much of the literature, the previous studies focused only on a small number of functions in integrating environmental management with HRM. Additionally, the measurement of green HRM practices still calls for empirical validation. The two‐stage methodology of structural equation modeling in AMOS was employed for data analysis. Exploratory factor analysis revealed seven dimensions of the construct measured by 28 items. Confirmatory factor analysis confirmed the factor structure. The measuring instruments revealed convergent and discriminant validity. Several model fit indices indicated the model fitness. The study provided supplementary evidence on the underlying structure of the construct that can be valuable to researchers and practitioners in this area.     

A spatial autoregressive stochastic frontier model for panel data incorporating a model of technical inefficiency

By integrating Battese and Coelli’s (1995) model and the spatial autoregressive model (SAR), a spatial autoregressive stochastic frontier model for panel data is developed. The main feature of this frontier model is a spatial lag term of explained variables and the joint structure of a production possibility frontier with a model of technical inefficiency. The model addresses both spatial dependence and heteroskedastic technical inefficiency. This study applies maximum likelihood methods considering the endogenous spatial lag term. The proposed model nests several existing models. Further, an empirical analysis using data on the Japanese manufacturing industry is conducted and the existing models are tested against the proposed model, which is found to be statistically supported. The findings suggest that estimates in the existing spatial and non-spatial models may exhibit bias because of lack of determinants of technical inefficiency, as well as a spatial lag. This bias also affects the technical efficiency score and its ranking.