Interviewer as instrument: accounting for human factors in evaluation research

This methodological study examines an original data collection model designed to incorporate human factors and enhance data richness in qualitative and evaluation research. Evidence supporting this model is drawn from in-depth youth and adult interviews in one of the largest policy/program evaluations undertaken in the United States, the Drug, Alcohol, and Tobacco Education evaluation (77 districts, 118 schools). When applying the explicit observation technique (EOT)--the strategic and nonjudgmental disclosure of nonverbal human factor cues by the interviewer to the respondent during interview--data revealed the observation disclosure pattern. Here, respondents linked perceptions with policy or program implementation or effectiveness evidence. Although more research is needed, it is concluded that the EOT yields richer data when compared with traditional semistructured interviews and, thus, holds promise to enhance qualitative and evaluation research methods. Validity and reliability as well as qualitative and evaluation research considerations are discussed.     

Transformational Leadership Education and Agency Perspectives in Business School Pedagogy: A Marriage of Inconvenience?

We critique transformational leadership education in university business schools based on a literature review, a study of the websites of 21 leading business schools, and an analysis of two presentations to business school students at Massachusetts Institute of Technology and Stanford University by the former CEO of General Electric, Jack Welch. Our critique draws attention to the unresolved tension between two motivating ideas that underpin much teaching in business schools: collective interest ideas that permeate transformational leadership education; and self-interest ideas derived from agency theory. Transformational leadership tends to be depicted as a process by which leaders exert a 'top-down' influence over the activities of others, while simultaneously asserting that their organizations have a common purpose and pursue a collective interest. We highlight the risk that business schools are producing graduates who will attempt to appeal to common needs (guided by precepts of transformational leadership) but who will simultaneously enact contradictory performance management systems (guided by agency theory). We encourage business school educators in leadership to adopt approaches which are more critical, relational and reflexive. We suggest some general directions for an alternative leadership prospectus, based on followership, the promotion of critical upward communication within organizations, and the recognition of leadership as a contested, discursive and co-constructed phenomenon.     

Uncertainty in competitive bidding – a framework for product–service systems

Owing to servitisation, manufacturing companies are increasingly required to compete through the provision of services around their products. The contracts for these services are often allocated through competitive bidding where the potential suppliers submit a price bid to the customer. The pricing decision is influenced by various uncertainties. This article proposes a conceptual framework depicting these influencing uncertainties on the bidding strategy. This framework is based on three empirical studies with industry investigating different viewpoints on the decision-making process. The intention is to support the pricing decision when competitively bidding for a service contract. The framework can be applied to specific competitive bidding situations to identify the influencing uncertainties, model them and depict their influences on the pricing decision.     

Reconceptualizing and expanding the positive feedback network effects model: A case study

During the 1980s, economists developed the concept of positive network effects and switching costs as the key dynamics of de facto standards competition. They concluded that a positive feedback loop usually “tips” a market to the standard with the most users and complementary assets. While recent scholars have acknowledged that not all markets tip, and suggested some possible limitations on this phenomena, these limitations have not been integrated systematically into a model for competition in these industries. Using examples drawn from the standards contests of the past 20 years, this case study develops an integrated model for competition in these industries.     

Categorizing Mistaken False Positives in Regulation of Human and Environmental Health

One of the concerns often voiced by critics of the precautionary principle is that a widespread regulatory application of the principle will lead to a large number of false positives (i.e., over-regulation of minor risks and regulation of nonexisting risks). The present article proposes a general definition of a regulatory false positive, and seeks to identify case studies that can be considered authentic regulatory false positives. Through a comprehensive review of the science policy literature for proclaimed false positives and interviews with authorities on regulation and the precautionary principle we identified 88 cases. Following a detailed analysis of these cases, we found that few of the cases mentioned in the literature can be considered to be authentic false positives. As a result, we have developed a number of different categories for these cases of "mistaken false positives," including: real risks, "The jury is still out," nonregulated proclaimed risks, "Too narrow a definition of risk," and risk-risk tradeoffs. These categories are defined and examples are presented in order to illustrate their key characteristics. On the basis of our analysis, we were able to identify only four cases that could be defined as regulatory false positives in the light of today's knowledge and recognized uncertainty: the Southern Corn Leaf Blight, the Swine Flu, Saccharin, and Food Irradiation in relation to consumer health. We conclude that concerns about false positives do not represent a reasonable argument against future application of the precautionary principle.     

Bootstrap Methods for Markov Processes

The block bootstrap is the best known bootstrap method for time‐series data when the analyst does not have a parametric model that reduces the data generation process to simple random sampling. However, the errors made by the block bootstrap converge to zero only slightly faster than those made by first‐order asymptotic approximations. This paper describes a bootstrap procedure for data that are generated by a Markov process or a process that can be approximated by a Markov process with sufficient accuracy. The procedure is based on estimating the Markov transition density nonparametrically. Bootstrap samples are obtained by sampling the process implied by the estimated transition density. Conditions are given under which the errors made by the Markov bootstrap converge to zero more rapidly than those made by the block bootstrap.