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Existing studies of ethnic voting mainly focus on democratic elections. In electoral autocracies, politically subordinate ethnicity can help citizens coordinate against the incumbent. However, we argue that collective action will be constrained when the group grows large, as it becomes costly for its members to form common behavioural norms and carry out effective sanctions through shared ethnic ties under authoritarian repression. Drawing on unique historical surveys in Taiwan, we study how Taiwanese ethnicity and local ethnic demography jointly induced voters' defection against the hegemonic KMT regime. We find that the pro-defection or anti-incumbent effect of Taiwanese ethnicity fell as the share of Taiwanese citizens in a township increased. However, the relative size of the Taiwanese group no longer undermined pro-defection ethnic voting after the KMT lifted the ban on opposition parties. Our results illustrate that formal organizations play a critical role in sustaining the informational salience of ethnicity in the elections.

PurposeThis research aims to determine to what extent uncertainties affected manufacturing enterprises' delivery performance, to analyse the performance of their contingency plans in dealing with uncertainties and to explore what technical and organisational factors affected managers' decisions to implement an uncertainty‐diagnosing model.Design/methodology/approachThe methodology included a literature review, postal questionnaire survey and telephone interviews.FindingsA total of 30 companies responded to the questionnaire, 56 per cent of which thought their systems worked well and 80 per cent reported that material shortages were responsible for tardy delivery performance. Tardy delivery was directly or indirectly caused by poor supplier delivery performance in the opinion of 92 per cent of respondents. Seven companies had developed an uncertainty‐diagnosing model. Not all companies needed to adopt the model.Research limitations/implicationsUncertainty and contingency plans were investigated in UK and Chinese organisations using MRP/MRPII/ERP systems. Therefore, the findings will be directly relevant to the organisations, but may be adapted to other similar organisations.Practical implicationsA detection method was proposed to determine the steps required for organisations to adopt the uncertainty‐diagnosing model.Originality/valueThe paper provides some empirical data on uncertainty and the contingency plans used in ERP‐controlled manufacturing environments in organisations in the UK and China. Data on uncertainty are scarce and this research gives further insights into the ways managers perceive and handle uncertainty.

In this study, we investigated how people evaluate behavioral interventions (BIs) that are targeted at themselves, aiming to promote their own health and wellbeing. We compared the impact on people's assessments of the acceptability of using BIs to change their own behavior of: the transparency of the BI (transparent or opaque); the designer of the BI (researchers, government policy-makers, advertisers); and three types of arguments regarding their efficacy (positive, positive + negative, negative). Our target BIs were actual interventions that have been used in a range of policy domains (diet, exercise, alcohol consumption, smoking, personal finances). We found that transparent BIs were considered more acceptable than opaque BIs. On average, all BIs were considered acceptable for changing participants' own behavior, except for the opaque BI in the finance context; there was differential acceptability of BIs across contexts, with finance clearly least acceptable. However, the perceived effectiveness of the BIs was at least as influential a predictor of acceptability ratings as the ease of identification of the behavior change mechanism across the five contexts. Furthermore, effectiveness was partially mediated by desire to change, suggesting that people do think BIs make them better off, 'as judged by themselves'.

Abstract. We developed a multi-scale OBIA (object-based image analysis) landslide detection technique to map shallow landslides in the Baichi watershed, Taiwan, after the 2004 Typhoon Aere event. Our semi-automated detection method selected multiple scales through landslide size statistics analysis for successive classification rounds. The detection performance achieved a modified success rate (MSR) of 86.5% with the training dataset and 86% with the validation dataset. This performance level was due to the multi-scale aspect of our methodology, as the MSR for single scale classification was substantially lower, even after spectral difference segmentation, with a maximum of 74%. Our multi-scale technique was capable of detecting landslides of varying sizes, including very small landslides, up to 95 m2. The method presented certain limitations: the thresholds we established for classification were specific to the study area, to the landslide type in the study area, and to the spectral characteristics of the satellite image. Because updating site-specific and image-specific classification thresholds is easy with OBIA software, our multi-scale technique is expected to be useful for mapping shallow landslides at watershed level.

The effect of online trading on investors' trading behavior is analyzed based on investors' trading data provided by a major security firm in Taiwan. Findings are as follows: (1) Male and younger traders preferred online trading. Investors who had a higher gross return tended to switch
to using online trading. (2) Even though investors traded more actively after going online, their trading performance was not negatively affected. (3) Online trading did not significantly increase speculative trading even though more information can be assessed online. (4) The order execution
efficiency of online trading was better than that of phone-based trading.