Employee acceptance of digital monitoring systems while working from home

Digitalisation and COVID-19 led to an expansion of remote work arrangements, raising the question of whether and how employers should monitor remote workplaces. However, before the implementation of monitoring methods, it is important to consider employees' acceptance of this approach. Therefore, we contribute to current research on electronic performance monitoring by empirically investigating employees' evaluations of performance monitoring at home. This paper presents an analysis of how certain monitoring technologies for work-from-home arrangements are perceived as undesirable and whether other job aspects can compensate for these unattractive monitoring components. Using an experimental factorial survey design, German employees evaluated remote work arrangements with randomly varying characteristics. We show that respondents accept a certain degree of monitoring at home but increasingly reject monitoring systems as they become more invasive. However, in some cases, the negative impact of monitoring at home can be mitigated by certain incentives, such as money or the purpose of monitoring.     

Consumer Response to a National Marketplace for Individual Health Insurance

The objective of this analysis is to simulate the difference between national and state‐specific individual insurance markets on take‐up of individual health insurance. This simulation analysis was completed in three steps. First, we reviewed the literature to characterize the state‐specific individual insurance markets with respect to state regulations and to identify the effect of those regulations on health insurance premiums. Second, we used empirical data to develop premium estimates for the simulation that reflect case‐mix as well as state‐specific differences in health care markets. Third, we used a revised version of the 2005 Medical Expenditure Panel Survey (MEPS) to complete a set of simulations to identify the impact of three different scenarios for national market development. (National market estimates are based on the simulation model with competition among all 50 states and moderate impact assumptions.) We find evidence of a significant opportunity to reduce the number of uninsured under a proposal to allow the purchase of health insurance across state lines. The best scenario to reduce the uninsured, numerically, is competition among all 50 states with one clear winner. The most pragmatic scenario, with a good impact, is one winner in each regional market.     

Bayesian regression with B‐splines under combinations of shape constraints and smoothness properties

In this paper, we approach the problem of shape constrained regression from a Bayesian perspective. A B‐splines basis is used to model the regression function. The smoothness of the regression function is controlled by the order of the B‐splines, and the shape is controlled by the shape of an associated control polygon. Controlling the shape of the control polygon reduces to some inequality constraints on the spline coefficients. Our approach enables us to take into account combinations of shape constraints and to localize each shape constraint on a given interval. The performance of our method is investigated through a simulation study. Applications to a real data sets in food industry and Global Warming are provided.     

Sectoral employment effects of trade and productivity in Europe

The impact of trade and technology in the European case is assessed. A framework is developed which incorporates employment effects of (i) export expansion (ii) import competition and (iii) labour-saving productivity improvements. In this context, evidence is found for the hypothesis that international trade induces adjustments in technology.     

Assessing Organizational Adoption of Information Systems Outsourcing

The information systems outsourcing (ISO) field continues to grow, as organizations consistently seek improvements in IT activities. The global scope of outsourcing participation and growth leads to gaps of knowledge related to the contextual factors that influence ISO adoption. Using the technology-organization-environment (TOE) framework, this study identifies and contextualizes the determinants of ISO adoption. Data collected from 261 firms suggest that relative advantage, firm size, top management support, and competitive pressure are the main determinants of ISO. This study highlights the importance of assessing ISO using the TOE theoretical lens, and offers replication of prior results, the lack of which is a growing concern in social science research.     

Statistics in Business and Industry: Implementation

There are many statistical tools available to be utilized for general business improvement and industrial problem solving. However, there is a wide gap between the tools available and those that are actually used in business and industrial organizations. Thus it is important for statisticians to direct serious attention to bridging this gap if statistics is to be relevant in business and industry. In this paper we look at some ideas for implementing statistical methods in business and industry.     

How CEOs and TMTs Build Adaptive Capacity in Small Entrepreneurial Firms

Research suggests that a CEO may have more influence in the context of small entrepreneurial firms, but it is still unclear how a company's chief executive facilitates strategic decision‐making. Little is known about the ways in which these individuals build strategic capabilities, such as the capacity to adapt to changing environments. This study addresses these issues and develops a model indicating that transformational leadership facilitates behavioural integration and comprehensiveness in the decision process among members of the top management team (TMT), which in turn enhances organizational capacity to adapt to environmental changes. Survey results shed light on the complex way in which CEOs facilitate processes within the TMT and enhance small entrepreneurial firms’ capacity to adapt, thereby increasing their viability. This study contributes to the literatures on Upper Echelon Theory, strategic decision‐making, and dynamic capabilities by shedding light on the ways in which transformational leaders influence behavioural and decision‐making processes.     

Pricing currency options with scheduled and unscheduled announcement effects on volatility

It is well documented that exchange rate volatility is time-varying and that it can be affected by scheduled events such as money supply announcements and unscheduled ones such as spot market interventions and interest rate changes. This study provides a European event model (E model) for currency call options that explicitly addresses the volatility effects of these two classes of events. Managers who are concerned with hedging in an environment of changing volatility may find the E model useful. The E and modified Black-Scholes (MBS) models have similar average errors in predicting option price changes across event windows and do better than a naive no-change prediction. The E model tends to reduce the underpricing of convex, short-term out-of-the-money options and the mispricing of most classes of convex options.