Technology improves sales performance—doesn't it?: An introduction to the special issue on selling and sales technology

Firms around the globe are rushing to invest in sales force technology or sales force automation (SFA). SFA appears to mean different things to different people. For example, management and sales personnel view the need for, application of, and advantages of SFA quite distinctly. As a result of technology, this special issue examines many areas of sales force automation to provide both practicing managers and sales force academicians with a clearer perspective of new technology in the B2B marketplace. This article introduces the special issue topic, individual contributors, and acknowledges support proffered by myriad individuals.     

Impact of sales force automation on technology-related stress, effort, and technology usage among salespeople

This study unveils factors affecting sales force automation (SFA) technology usage by salespeople. It differs from previous research by: (1) proposing a model that examines the consequences of task complexity on role perceptions and technology usage, and (2) understanding the negative repercussions of SFA technology on the user. The proposed model was tested using data from 150 salespeople employed by a national organization. The results suggest that integration of SFA technology induces adverse role perceptions in salespeople. However, controlling for extraneous variables, effort is significantly related to salespeople's usage of technology. Key managerial implications for theory and practice are discussed.     

Sales force technology usage—reasons, barriers, and support: An exploratory investigation

Increasingly, salespeople are being asked to adopt and use a variety of technologies to increase their selling productivity and efficiency, including sales force automation and customer relationship management technologies. However, little research has investigated what happens once sales force automation (SFA) technology is adopted. This paper explores the reasons why salespeople use SFA technologies, the perceived barriers to SFA usage and how management can increase the usage of SFA technology. First, a qualitative study was performed to gain insight about salespeople's automation technology usage and the reasons why some salespeople fully use or do not utilize technology. After the initial study, 130 salespeople were surveyed. More productivity/efficiency was the main reason why salespeople use technology, the lack of management and technical support proved to be the main barrier to usage, and training proved most effective in increasing usage of SFA technology. Sales managers are provided with implications of the findings.     

Expected exponential utility maximization of insurers with a Linear Gaussian stochastic factor model

In this paper, we consider the problem of optimal investment by an insurer. The wealth of the insurer is described by a Cramér–Lundberg process. The insurer invests in a market consisting of a bank account and m risky assets. The mean returns and volatilities of the risky assets depend linearly on economic factors that are formulated as the solutions of linear stochastic differential equations. Moreover, the insurer preferences are exponential. With this setting, a Hamilton–Jacobi–Bellman equation that is derived via a dynamic programming approach has an explicit solution found by solving the matrix Riccati equation. Hence, the optimal strategy can be constructed explicitly. Finally, we present some numerical results related to the value function and the ruin probability using the optimal strategy.     

New development: Regression-to-the-mean explains the otherwise puzzling coefficients in NHS England’s formula for funding CCGs

This paper reviews NHS England’s recent report on the formula that guides the allocation of tens of billions of pounds to clinical commissioning groups (CCGs). It finds deficiencies and errors in the unprincipled construction of the formula and substitutes Sir Francis Galton’s logical concept of ‘regression to the mean’ for the report’s ad hoc conjectures about striking patterns of certain coefficients.     

Pricing mortgage insurance contracts under housing price cycles with jump risk: evidence from the U.K. housing market

Previous studies have investigated the determinants of housing price cycles in the housing market; however, we observed the phenomenon of housing price jumps in the 2007 subprime crisis. This paper presents a discussion on the housing price cycle and abnormal price jumps to describe the behavior of housing prices in the United Kingdom. The empirical results show that the impact factors of housing cycles are market risk and the switching factor. Furthermore, the impact factors of jump risks include the bursting of the housing bubble and financial crises. Therefore, in this paper, we employ the Markov switching model with jump risks to value the MI contracts and analyze the influences of housing price cycles, jump risks, risks of market interest rate, and the prepayment risks on MI premiums. The results of sensitivity analysis show that more volatile housing price index returns, as well as longer periods of higher volatility in housing prices, raise MI premiums. Moreover, the MI premium is positively related to the absolute value of the average jump amplitude and the shock frequency of abnormal events. There is the tradeoff between the market interest rate and the prepayment risk. The influences of market interest rate are different on MI premium with/without prepayment risks.     

Why are there time-varying comovements in the European stock market?

This paper analyzes the dynamics of pair comovements between different domestic European stock market returns (Spain, France, Germany, Switzerland and the United Kingdom) seeking to check whether there is a unique source of risk driving those dynamics. Once it is shown that the comovements are time-varying, the question is to find whether a global index such as the Euro Stoxx can be considered the main source of risk. To that end we estimate and test for time-varying global pair covariances and for time-varying remaining pair covariances once the effect of the Euro Stoxx is removed. The empirical results are obtained considering locally stationary variables, a family that includes variables with first and second time-varying moments. Under that framework time-varying means and covariances can be estimated using a spline-based procedure and Wald-type statistics can be computed to test for time-variations. A simulation study shows that the role of the mean estimation part is crucial to the good performance of the tests for second moments. The empirical results evidence that all global pair covariances for the European countries analyzed are time-varying, but also that the Euro Stoxx can be considered as the driving source of risk for these time-varying dynamics. This conclusion is very useful for modeling purpose and financial strategies. Finally, we repeat the analysis considering the Nasdaq as an alternative global index and find that it explains only a small part of the dynamics in the European pair comovements.     

Globalization and Outward Foreign Direct Investment

While recent research into foreign direct investment (FDI) has focused on examining the importance of institutions, corruption, money laundering, and tax havens, the role of globalization on FDI has not yet been explored. This research investigates the impacts of globalization on outward FDI. We find that both overall globalization and its economic and social dimensions significantly positively influence outward FDI flows. We also demonstrate that beyond the level of globalization, corruption, money laundering, and the status of a country as a tax haven, cross-country similarity also plays an important role. Accordingly, policies specifically designed to increase the transparency of outward FDI flows should be required to address money laundering and the existence of tax havens.     

Export Sophistication: A Dynamic Panel Data Approach

In this article, we analyze export sophistication based on a large panel dataset (2001–2015; 101 countries) and using various estimation algorithms. Using Monte Carlo simulations, we evaluate the bias properties of estimators and show that GMM-type estimators outperform instrumental-variable and fixed-effects estimators. Based on our analysis we document that GDP per capita and the size of the economy exhibit significant and positive effects on export sophistication; weak institutional quality exhibits negative effect. We also show that export sophistication is path-dependent and stable even during a major economic crisis, which is especially important for emerging and developing economies.     

Liquidity operations during the financial crisis 2008/09: evidence from the relations between Korean won onshore and offshore markets

This paper addresses the interrelation of onshore and offshore markets before and after the Bank of Korea intervened in 2008/09. During the financial crisis, Korea faced a liquidity crunch and leveraged its high level of reserves to conduct swap agreements in late 2008. To analyse how the reforms affected the mean and volatility spillover in between the spot and NDF markets, an extended GARCH model is used. The main findings of this paper are that prior to the financial crisis, the spot market dominated the offshore market. This changed after South Korea addressed the won’s liquidity crunch at the height of the crisis. Mean and volatility spillover between the markets diminished and the price gap narrowed. In addition to the empirical results, the paper also underlines the significance of liquidity and robust capital requirements for central banks.