Testing the Influence of Substitute Sites in Nature Valuation by Using Spatial Discounting Factors

This paper investigates the effect of nearby nature substitute sites on preferences for nature restoration. Contrary to prior studies, we use a respondent-centric approach to control for substitute sites. We assess each respondent-specific spatial context by computing densities of nature substitute sites within various ranges from each respondent’s home. This approach considers the use and non-use values of nature together. Data from three similar discrete choice experiments carried out in Flanders (Belgium) are compared. Different spatial discounting factors are tested to explore how the substitution effect behaves with regard to distance. Latent class analyses are performed to account for preference heterogeneity among respondents. We observe divergent behaviours across groups of respondents. The “distance-to-substitutes” affects how respondents gauge substitute sites. We find a significant influence of the squared average buffer distance but this effect varies in sign across case studies and classes of respondents. Our results demonstrate that individual-specific GIS data can significantly improve the representation of the spatial context and the transferability of value functions. However, the roles played by preference heterogeneity and nature perception on respondents’ capacity to value nature still deserves further attention in future research.     

Do economic statistics contain information to predict stock indexes futures prices and returns? Evidence from Asian equity futures markets

This research examines the impact of local and international market factors on the pricing of stock indexes futures in East Asian countries. The purpose of this paper is to present a study of the significant factors that determine the major stock indexes futures’ prices of Hong Kong, Malaysia, Singapore, South Korea and Taiwan. This study first investigates the relationships between Hang Seng Index Futures, KLCI Futures, SiMSCI Futures, KOSPI Futures, Taiwan Exchange Index Futures and local interest rates, dividend yields, local exchange rates, overnight S&P500 index and a newly constructed index, Asian Tigers Malaysia Index (ATMI). 11 years historical data of stock indexes futures and the economic statistics are studied; 10 years in-sample data are used for testing and developing the pricing models, and 1 year out-of-sample data is used for the purpose of verifying the predicted values of the stock indexes futures. Using simple linear regressions, local interest rates, dividend yields, exchange rates, overnight S&P500 and ATMI are found to have significant impact on these futures contracts. In this research, the next period close is predicted using simple linear regression and non-linear artificial neural network (ANN). An examination of the prediction results using nonlinear autoregressive ANN with exogenous inputs (NARX) shows significant abnormal returns above the passive threshold buy and hold market returns and also above the profits of simple linear regression (SLR). The empirical evidence of this research suggests that economic statistics contain information which can be extracted using a hybrid SLR and NARX trading model to predict futures prices with some degree of confidence for a year forward. This justifies further research and development of pricing models using fundamentally significant economic determinants to predict futures prices.

     

Dependence of the Russian defense industry on oil prices: Conversion

The article analyzes the impact of the collapse of world oil prices on the reduction of defense budget, production of weapons, innovative and personnel potential of the defense industry, and on country’s defense capability. Some proposals for the concept of structural changes in the defense industry have been formulated based on experience converting the defense industries in the Soviet Union, the United States, China, and France.     

Life Expectancy Heterogeneity and the Political Support for Collective Annuities

Individuals, differing in productivity and life expectancy, vote over the size and type of a collective annuity. Its type is represented by the fraction of the contributive (Bismarckian) component (based on the worker's past earnings) as opposed to the non‐contributive (Beveridgean) part (based on average contribution). The equilibrium collective annuity is either a large mostly Bismarckian program, a smaller pure Beveridgean one (in accordance with empirical evidence), or nil. A larger correlation between longevity and productivity, or a larger average life expectancy, both make the equilibrium collective annuity program more Beveridgean, although at the expense of its size.     

On Some Characteristics of Gaussian Covariance Functions

The concepts of isotropy/anisotropy and separability/non‐separability of a covariance function are strictly related. If a covariance function is separable, it cannot be isotropic or geometrically anisotropic, except for the Gaussian covariance function, which is the only model both separable and isotropic. In this paper, some interesting results concerning the Gaussian covariance model and its properties related to isotropy and separability are given, and moreover, some examples are provided. Finally, a discussion on asymmetric models, with Gaussian marginals, is furnished and the strictly positive definiteness condition is discussed.     

On Measurement of Economic Growth

This article continues the discussion raised in the pages of the journal on the methodological problems of justifying economic policy [1]. Problems of measuring the inflationary component of economic growth and in product competitiveness in the internal market and external markets are considered. A procedure to measure economic growth, taking into account the balance of interests of the current and future generations, is proposed.     

Could lean practices and process innovation enhance supply chain sustainability of small and medium‐sized enterprises?

Small and medium‐sized enterprises (SMEs) adopt lean practices (LP) to reduce waste across their organisational value chain, which helps achieve sustainability. Process innovation (PI) has also been applied through cleaner production, environmental management system, ecodesign, and so on to address both customers' needs and legislations by policymakers. Although prior studies reveal the effect of sustainable practices, LP, and PI on sustainable performance separately, less is known on the integrated effect of them on sustainability performance. Moreover, studies on mediating effect of LP and PI on sustainability performance are scant. This is significant as LP and PI are considered to be the enablers for achieving sustainability performance. This research addresses this knowledge gap. The research first theorises a model integrating these four major constructs (sustainability practices, LP, PI, and sustainability performance) through hypotheses development. Subsequently, using structural equation modelling, it is tested whether each of sustainability practices, LP, and PI effect sustainability performances. Additionally, mediating effect of LP and PI between sustainability practices and performances is derived. The study uses data from 119 SMEs within manufacturing industries in the Midlands, United Kingdom. Further, a few case studies have been undertaken to validate the findings from quantitative analysis. The overall results show that although sustainability practices, LP, and PI help achieve sustainability performance of SMEs supply chain through efficiency and responsiveness respectively, the mediating effect LP is more compared with PI. Moreover, SMEs adopt LP when they are economy focused and implement PI when they are pressurised by customers and/or policymakers.     

A Note on Family Influence and the Adoption of Discontinuous Technologies in Family Firms

The 4Cs model of command, continuity, community, and connections is useful for examining the effect of family influence on the adoption of discontinuous technologies. However, assuming that family influence differs only in degree rather than kind is naive because such an assumption ignores the likelihood of heterogeneous behaviors among family firms. In this conceptual note, we extend prior work and explain how heterogeneity in the family's relative emphasis on command, continuity, community, and connections requires that the multifaceted and potentially nonlinear nature of family influence be considered when analyzing strategic decisions concerning family firm innovation.     

Digital Transformation Through Exploratory and Exploitative Internet of Things Innovations: The Impact of Family Management and Technological Diversification*

This study examines the impact of family management on digital transformation with specific regard to the firm’s development of Internet of Things (IoT) innovations. Drawing on the distinctive characteristics of firms with family managers, such as the focus on family‐centered noneconomic goals, long tenure, emotional ties to existing assets, and rigid mental models, it hypothesizes that increasing family involvement in the top management team is negatively related to the development of IoT innovations that are distant from a firm’s existing technology base (i.e., exploratory IoT innovations) compared to exploitative IoT innovations. Further, the study proposes that the firm’s degree of technological diversification, especially in unrelated forms, reinforces this relationship. The longitudinal analysis between 2002 and 2013 on a sample of publicly traded German firms allows us to test our hypotheses from the beginning of the emergence of the IoT concept. Our findings show that due to the particular characteristics of their managers, family‐managed firms do not welcome the risks related to exploratory IoT innovations, and the benefit of risk diversification from technological diversification is lower than the cost of abandoning family‐centered goals. As our results imply that the involvement of family managers constrains the development of exploratory IoT innovation, the top management team composition in firms that intend to be at the forefront of the digital transformation should be accurately designed by avoiding a high proportion of family members.