Exploring Attitudes Toward Aquaculture Development in the United Kingdom: A Consultative Stakeholder Approach

ABSTRACT

This study explores attitudes toward aquaculture development as a way of providing a sustainable source of seafood through a consultative stakeholder approach. Given that aquaculture is a less familiar concept within southwest England, gaining insight into the views and perspectives of such a development in the region is required to facilitate stakeholder engagement. In-depth qualitative interviews investigate attitudes across five stakeholder sectors: government, fishing/marine, business/catering, tourism/leisure, and environmental/charity. Findings show a mix of stakeholder attitudes, which differ by industry sector, from very negative to very positive. From this, two segments are proposed (commercially focused and environmentally focused) to enable targeted communication and information dissemination strategies based on key areas of concern.     

CUTTING LOGISTICS COSTS WITH OCEAN CARRIER SELECTION

Two decades of survey research has shown that transit‐time differences among ocean carriers are often secondary considerations in carrier selection. However, this study found that shippers can pay substantial premiums for superior ocean transit‐time service, and cut logistics costs even when substantial variability occurs in landside segments of supply chains.     

The geography of market failure: Edge-effect externalities and the location and production patterns of organic farming

Perceptions of increasing land scarcity and negative impacts of chemical-based agriculture have led to increasing concern regarding the sustainability of food systems. Incompatible production processes among farming systems may lead to spatial conflicts and production losses between neighboring farms, and the magnitude of such losses may depend not only on the scale of each activity, but also on patterns of land use. Such conflicts can be classified as “edge-effect externalities”—spatial externalities whose marginal impacts decrease as distance from the border generating the negative impact increases. This paper tests the hypothesis that edge-effect externalities have influenced the location and production patterns of certified organic farms, using data from California Central Valley certified organic farmers. Using concepts from landscape ecology and spatial statistics, we investigate difference in parcel geometry and surrounding land uses between organic and non-organic parcels. Using a generalized method of moments (GMM) spatially autoregressive econometric model, we demonstrate that both parcel geometry and surrounding land uses influence the probability of a given parcel being certified organic. We conclude with suggestions for policies to encourage development of organic farming regions.     

Reconceptualizing entrepreneurial exit: Divergent exit routes and their drivers

We develop a conceptual model of entrepreneurial exit which includes exit through liquidation and firm sale for both firms in financial distress and firms performing well. This represents four distinct exit routes. In developing the model, we complement the prevailing theoretical framework of exit as a utility-maximizing problem among entrepreneurs with prospect theory and its recent applications in liquidation of investment decisions. We empirically test the model using two Swedish databases which follow 1,735 new ventures and their founders over eight years. We find that entrepreneurs exit from both firms in financial distress and firms performing well. In addition, commonly examined human capital factors (entrepreneurial experience, age, education) and failure-avoidance strategies (outside job, reinvestment) differ substantially across the four exit routes, explaining some of the discrepancies in earlier studies.     

Entrepreneurial exit as a critical component of the entrepreneurial process: Theoretical development

By demonstrating the importance of entrepreneurial exit to the entrepreneur, the firm, the industry, and the economy I contend that our understanding of the entrepreneurial process is incomplete without the inclusion of entrepreneurial exit. I define entrepreneurial exit and demonstrate how this conceptualization provides concepts that are unique from those addressed by researchers in other domains; thus outlining a space for it within the literature. In each phase of the entrepreneurial process I explore the development of an exit strategy, reasons for exit and options for exit.     

Specificity of CEO human capital and compensation

Much research on top management compensation has focused on the relationship between pay and firm performance. Firms, however, may compensate executives for inputs such as skills, as well as for outputs such as firm performance. This study refocuses attention on the links between managerial abilities and compensation by examining pay differences between types of CEO successors who have differential skills—namely, internal and external successors. © 1997 John Wiley & Sons, Ltd.     

A psychometric assessment of the Lennox and Wolfe self-monitoring scale in the sales force

In today's turbulent business environment, salespeople and sales managers must constantly adapt to changes. Self-monitoring, i.e., the cognitive ability to adapt one's own behavior in response to the behavior of others, may be a meta-KSA (knowledge, skill, or ability) that influences adaptive selling behavior. To assist researchers and practitioners seeking to identify and improve the self-monitoring skills of salespeople, this study investigates Lennox and Wolfe's (1984) self-monitoring scale with a sample of salespeople and one with sales managers. Although a hypothesized relationship between self-monitoring and job performance was supported partially, our results highlight potential problems with the measure. Further investigations are needed to determine whether or not the problems lie with the scale or the concept of self-monitoring in a selling context.     

Evaluating the performance of a predictive modeling approach to identifying members at high-risk of hospitalization

Abstract

Aims: To evaluate the risk-of-hospitalization (ROH) models developed at Blue Cross Blue Shield of Louisiana (BCBSLA) and compare this approach to the DxCG risk-score algorithms utilized by many health plans.

Materials and Methods: Time zero for this study was December 31, 2016. BCBSLA members were eligible for study inclusion if they were fully insured; aged 80?years or younger; and had continuous enrollment starting on or before June 1, 2016, through time zero. Up to 2?years of historical claims data from time zero per patient was included for model development. Members were excluded if they had cancer, renal failure, or were admitted for hospice. The Blue Cross ROH models were developed using (1) regularized logistic regression and (2) random decision forests (a tree ensemble learning classification method). All models were generated using Scikit-learn: Machine Learning in Python. Prognostic capabilities of DxCG risk-score algorithms were compared to those of the Blue Cross models.

Results: When stratifying by the top 0.1% of members with the highest ROH, the Blue Cross logistic regression model had the highest area under the receiving operator characteristics curve (0.862) based on the result of 10-fold cross-validation. The Blue Cross random decision forests model had the highest positive predictive value (49.0%) and positive likelihood ratio (61.4), but sensitivity, specificity, negative predictive values, and negative likelihood ratios were similar across all four models.

Limitations: The Blue Cross ROH models were developed and evaluated using BCBSLA data, and predictive power may fluctuate if applied to other databases.

Conclusions: The predictability of the Blue Cross models show how member-specific, regional data can be used to accurately identify patients with a high ROH, which may allow healthcare workers to intervene earlier and subsequently reduce the healthcare burden for patients and providers.