Automated computer-based detection of encounter behaviours in groups of honeybees.

Honeybees form societies in which thousands of members integrate their behaviours to act as a single functional unit. We have little knowledge on how the collaborative features are regulated by workers' activities because we lack methods that enable collection of simultaneous and continuous behavioural information for each worker bee. In this study, we introduce the Bee Behavioral Annotation System (BBAS), which enables the automated detection of bees' behaviours in small observation hives. Continuous information on position and orientation were obtained by marking worker bees with 2D barcodes in a small observation hive. We computed behavioural and social features from the tracking information to train a behaviour classifier for encounter behaviours (interaction of workers via antennation) using a machine learning-based system. The classifier correctly detected 93% of the encounter behaviours in a group of bees, whereas 13% of the falsely classified behaviours were unrelated to encounter behaviours. The possibility of building accurate classifiers for automatically annotating behaviours may allow for the examination of individual behaviours of worker bees in the social environments of small observation hives. We envisage that BBAS will be a powerful tool for detecting the effects of experimental manipulation of social attributes and sub-lethal effects of pesticides on behaviour

Technology readiness: a meta-analysis of conceptualizations of the construct and its impact on technology usage

The technology readiness (TR) index aims to better understand people’s propensity to embrace and use cutting-edge technologies. The initial TR construct considers four dimensions—innovativeness, optimism, insecurity, and discomfort—that collectively explain technology usage. The present meta-analysis advances understanding of TR by reexamining its dimensionality, and investigating mediating mechanisms and moderating influences in the TR–technology usage relationship. Using data from 193 independent samples extracted from 163 articles reported by 69,263 individuals, we find that TR is best conceptualized as a two-dimensional construct differentiating between motivators (innovativeness, optimism) and inhibitors (insecurity, discomfort). We observe strong indirect effects of these dimensions on technology usage through mediators proposed by the quality–value–satisfaction chain and technology acceptance model. The results suggest stronger relationships for motivators than for inhibitors, but also that these TR dimensions exert influence through different mediators. Further, the moderator results suggest that the strength of TR–technology usage relationships depends on the technology type (hedonic/utilitarian), examined firm characteristics (voluntary/mandatory use; firm support), and country context (gross domestic product; human development). Finally, customer age, education, and experience are related to TR. These findings enhance managers’ understanding of how TR influences technology usage

Testing retail marketing-mix effects on patronage: A meta-analysis

Retailers have always worked to establish close relationships with customers through the retail marketing mix. Thus, the literature has a long tradition of testing the effects of various instruments on retail patronage. This meta-study synthesizes prior research into one comprehensive framework. We use 14,895 effect sizes reported by more than 239,000 shoppers from 41 countries extracted from 350 independent samples, to test the impact of 24 marketing-mix instruments on retail patronage. Specifically, we investigate the direct and indirect effects of these instruments on store satisfaction, word of mouth, patronage intention, and behavior. Product and brand management related instruments display the strongest effects on most outcome variables, whereas price, communication, service and incentive management instruments affect only selected outcomes. Distribution management turns out to be of secondary importance. However, the effectiveness of these instruments depends on the specific shopping context (food/non-food, shopping frequency, single store/agglomeration, hedonic/utilitarian), the retail environment (gross domestic product, country innovativeness, retail sales share, retail employment, Internet era), and the employed method (participant type, study design, data source). Specifically, we reveal most differences for hedonic shopping environments and developed countries. Also, the store’s advertising and atmosphere have gained importance in the Internet era, while purchase incentives, in-store orientation, and store location have lost relevance. This study contributes to a synoptic understanding of the comparable effectiveness of retail marketing instruments on retail patronage. It offers insights into the effectiveness of marketing-mix instruments and provides guidance on whether and when to invest in them. It also presents an agenda for future research on marketing-mix instruments

Complaint handling in the B2B sector

This paper describes complaint handling in the B2B sector