PurposeAdvances in technologies have allowed service providers to incorporate many different technologies into the delivery of their services. These technologies have been implemented in the service encounter for the customer to use with varying degrees of success. This research aims to focus on the examination of factors that influence consumer attitudes toward, and adoption of, self‐service technologies (SSTs).Design/methodology/approachA conceptual model of the adoption process for SSTs is developed and tested across three different technologies used in the banking industry. One of these technologies (ATMs) has been available for many years and is widely adopted, another technology (bank by phone) has been available for many years but has not been widely adopted, and the third technology (online banking) is relatively new to the marketplace. Data were collected using a random telephone survey of banking customers in a three‐state area of the northeast USA and analyzed using structural equation modeling.FindingsA comparison of the results of the model tests on the three technologies provides evidence that different factors influence attitudes toward each of these technologies and offers an explanation of the varying degrees of acceptance found among consumers. This research has demonstrated that multiple factors need to be considered when introducing technologies into the service encounter and that the salient factors may vary among technologies and their stages in the adoption process.Research limitations/implicationsThe three different technologies used were all based in the banking industry, which limits the generalizability to other industries. Also cross‐sectional data are used rather than a longitudinal study, the feasibility of which is limited by time and cost contraints.Originality/valueThe practical application of these findings may guide marketers to emphasize issues related to certain critical constructs when utilizing SSTs in their service delivery.

The introduction of self-service technologies (SSTs) into the service encounter necessitates research to better understand customers’ attitudes toward service providers and technologies, and their intentions to use technology-based service delivery systems. In this research, the authors develop and empirically test three nested structural models that include a hierarchy of consumer attitudes toward both the interpersonal and the technological aspects of the encounter to better understand their intentions to use SSTs. The findings indicate that intentions to use SST options are driven by multiple, hierarchical attitudes. In addition to the direct effects of attitudes toward specific SSTs and individual employees, the findings confirm that higher order global attitudes toward service technologies influence intentions to use SSTs. Interestingly, the findings indicate that heavy SST users rely more on attitudes toward specific SSTs than do light SST users, who rely more heavily on global attitudes toward SSTs when determining intention to use an SST.

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The interpretation of matching between DNA profiles of a person of interest and an item of evidence is undertaken using population genetic models to predict the probability of matching by chance. Calculation of matching probabilities is straightforward if allelic probabilities are known, or can be estimated, in the relevant population. It is more often the case, however, that the relevant population has not been sampled and allele frequencies are available only from a broader collection of populations as might be represented in a national or regional database. Variation of allele probabilities among the relevant populations is quantified by the population structure quantity FST and this quanity affects matching propoptions. Matching within a population can be interpreted only with respect to matching between populations and we show here that FST, can be estimated from sample allelic matching proportions within and between populations. We report such estimates from data we extracted from 250 papers in the forensic literature, representing STR profiles at up to 24 loci from nearly 500,000 people in 446 different populations. The results suggest that theta values in current forensic use do not have the buffer of conservativism often thought.

DNA profiles from multiple-contributor samples are interpreted by comparing the probabilities of the profiles under alternative propositions. The propositions may specify some known contributors to the sample and may also specify a number of unknown contributors. The probability of the alleles carried by the set of people, known or unknown, depends on the allelic frequencies and also upon any relationships among the people. Membership of the same subpopulation implies a relationship from a shared evolutionary history, and this effect has been incorporated into the probabilities. This acknowledgment of the effects of population structure requires account to be taken of all people in a subpopulation who are typed, whether or not they contributed to the sample.

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