Determining the Key Factors of Customer–Brand Relationship Investment Dimensions: Insights From Malaysian Mobile Phone Users

This study aims to empirically test a scale to measure the dimensions of relationship investment. An exploratory factor analysis and reliability analysis were conducted on a sample of 150 mobile phone customers, whereas a confirmatory factor analysis was conducted on a sample of 539 customers. The results identified 2 dimensions each for customer and brand investment and validated the measurement items for each dimension. Thus, this study offers a sound scale for potential use in future studies and a useful tool for companies to use to diagnose and plan for an effective engagement strategy.     

APPLYING SOCIAL NETWORK ANALYSIS TO INPUT–OUTPUT BASED INNOVATION MATRICES: AN ILLUSTRATIVE APPLICATION TO SIX OECD TECHNOLOGICAL SYSTEMS FOR THE MIDDLE 1990s

The paper discusses, illustrates and possibly contributes to overcoming two methodological problems that emerge in applying Social Network Analysis (SNA) to the study of IO-based innovation flows matrices. The first has to do with the scale-effects these matrices suffer from. The second refers to the need of dichotomising the matrices. Through an illustrative application to six OECD countries in the mid-1990s, the paper shows that, as for the former problem, different relativisation procedures can be, and have been, used, which either tend to alter the actual meaning of standard SNA indicators, or do not properly take into account the actual composition of countries' final demand. As for the latter problem, the paper shows that the choice of discrete cut-offs is extremely sensitive, as comparative results actually change along the continuum of the matrices values. In order to overcome the scale problem, a new relativisation procedure is put forward that measures innovation flows embodied in a unit value basket of final demand and thus properly retains all the information provided by the original matrix of intersectoral innovation (embodied) flows. In addressing the problem of dichotomisation, the paper suggests, as a second best, to work with density distributions that can make the choice of discrete cut-off values less arbitrary.     

Why does the trend extracted by the Hodrick–Prescott filtering seem to be more plausible than the linear trend?

Why does the trend extracted by the Hodrick–Prescott (HP) filtering (HP trend) seem to be more plausible than the linear trend estimated by OLS? This article provides an answer for it. Because the HP filtering is a basic econometric tool, it is necessary to have a precise understanding of the nature of it. This article concludes that the HP trend is calculated by adding the low-frequency component (the long-term periodic fluctuation) of the linearly detrended series to the linear trend, which leads to that the HP trend seems to be more plausible than the linear trend. Other than this key result, this article shows that the HP cycle, which is defined as the residuals of the HP filtering, can be interpreted as the high-frequency component (the short-term periodic fluctuation) of the linearly detrended series. An empirical illustration is also provided.     

Saving,investment and capital mobility in EU member countries: a panel data analysis of the Feldstein–Horioka puzzle

ABSTRACT

In this paper, we reexamine the long-standing and puzzling correlation between national saving and investment in 14 European Union (EU) countries. We employ a panel data set for the period 1970–2015 and we apply recently developed maximum likelihood panel cointegration methodologies. We find that there exists a long-run relationship between savings and investment for this panel of EU member countries, with the savings retention coefficient being low in magnitude but statistically different than zero. Therefore, we argue that there is weak evidence in favour of the Feldstein–Horioka puzzle and that the long-run international solvency condition is maintained in most of these countries. This evidence implies a moderate degree of capital mobility which is consistent with the macroeconomic experience of these countries during the period under investigation.     

Resources,home institutional context and SMEs’ exporting: Direct relationships and contingency effects

Research highlights the role of resources in SMEs’ exporting but is less forthcoming with respect to entrepreneurial perceptions of home institutional quality. Drawing on institution-based lenses, we distinguish among formal, informal, and regulatory institutions, which in concert with firm resources are expected to influence SMEs’ export behavior. Our predictions are tested on a sample of 150 firms located in Greece. The analysis of direct relationships shows that formal and informal institutional dimensions affect significantly, but differently, SMEs’ export activity. The analysis of interaction effects demonstrates that resource decisions for exporting are contingent upon entrepreneurial perceptions of the home institutional context, such that SMEs respond to formal and informal domestic institutional weaknesses by intensifying resource allocations to fuel export sales. In an opposite direction, export regulatory complexity reverses the positive resources-exporting link. These findings suggest the importance of home institutions in the exporting field.     

Bifurcations in the evolutionary approach to multilateralizing trade policy

The Doha Round on multilateral trade liberalization, originally intended to better integrate developing countries into the world economy, has been largely considered a failure. With the Doha outcome falling short of expectations, North–South trade remains underdeveloped. Embedding the political economy and the resulting importance of reciprocating trade liberalization in an evolutionary model along Axelrod–Rapoport lines indicates that factor endowments are crucial in triggering trade policies. Their pivotal nature gives rise to bifurcations, thereby tilting policies towards or away from liberalization trajectories. The theoretical insights are reflected in an empirical analysis, thus strengthening the case for a variable-geometry approach.     

A new perspective on the third-country effect: The case of Malaysia–US industry-level trade

Cushman suggested that impact of exchange rate volatility declines after the inclusion of the third-country effect. Like Cushman, when we use a linear analysis, we confirm his results. However, when we engage in asymmetric effects of exchange rate volatility which requires including nonlinear adjustment of volatility measures, the findings show more support to both exchange rate volatility influence and the third-country effect. Therefore, we propose that in examining exchange rate volatility effect on trade, consideration must be given to not just asymmetric effects of exchange rate volatility but also asymmetric effects of the third-country effect. We demonstrate these findings using monthly data from 54 Malaysian industries that export to the US and 63 Malaysian industries that import from the US.     

Strong–weak collaborative management in coping supply chain disruption risk transmission based on scale-free networks

Supply chain disruption causes tremendous loss to supply chains and global businesses. Organizational structure and operational features of supply chain networks, therefore, constitute a major portion of research for coping with supply chain disruption risk. This article first discusses the theoretical foundation, analyses the strength theory of strong and weak ties and the collaborative theory of strong and weak ties. Also, research methods are explicated; the scale-free networks and the theory of strong ties are integrated; the features of supply chain networks are considered from single statistical parameters and comprehensive analyses. Next, we provide numeric simulation of the properties of supply chain networks, verifying the accuracy of parameter analyses of single statistics and comprehensive analyses. Ultimately, when coping with supply chain disruption risk, each node enterprise of supply chain network is supposed to deploy the characteristics of scale-free networks to systematically manage existing weak ties, weak ties newly introduced, existing strong ties and strong ties newly introduced. This study is conducive to node enterprises of supply chains to recognize and apply the scale-free networks and the strength theory of ties to analyze the properties of supply chain networks, and to improve the capacity to cope with disruption risk.     

Predicting the competitive relationships of industrial production between Taiwan and China using Lotka–Volterra model

This work is the first to apply Lotka–Volterra model combined with genetic algorithm (GA) to predict the production relationships of high-tech industry among different areas. Previous studies analysed the trade interdependency among various countries, but few studies have highlighted the quantitative evidence of production relationships. Thus, this study utilizes motherboard shipment volumes to predict the competitive relationships of industrial production on both sides of the Taiwan Strait. Specifically, this work uses simultaneous non-linear least square regression in combination with GAs for numerical parameter optimization of the proposed Lotka–Volterra model. The results of parameter estimation reveal that shipment growth in China substantially promotes that in Taiwan, whereas the shipment growth in Taiwan curtails that in China. The standard deviation of the estimated parameters from the 3000 iterated simulations is small, confirming the reliability and stability of our parameter estimations. According to equilibrium analysis, the results of Lyapunov function prove that the shipments of China and Taiwan will reach a stable long-term equilibrium. The potential production from China will ultimately be nearly 16 times as large as that from Taiwan. Finally, the analytical results of forecast accuracy confirm that Lotka–Volterra model performs better than conventional S-curve diffusion model in predicting motherboard shipments.     

Contingent Labor and Higher Education

Over the past 30 years, the profession of college professor in the US has been changing from a high-status occupation, where faculty have extensive control over their job responsibilities, to a low-status contingent job in the peripheral labor market. This change mirrors the drift toward nonstandard employment in other sectors of the economy. Contingent and part-time faculty have grown at 10 times the rate of growth for tenure-track faculty, leading to a fundamental transformation in the nature of the professoriate. We review data related to these changes as well as the conventional explanations for this transformation. We conclude that the current system of academic labor is best understood within the core–periphery model of nonstandard employment. We conclude with some brief prospects for the future of the academic labor market and higher education.