An Empirical Study of the Impact of the Choice of Persistence Models in Value Added Modeling upon Teacher Effect Estimates

Author(s):  
Yong Luo ◽  
Hong Jiao ◽  
Robert Lissitz
Author(s):  
Keng-Lin Soh ◽  
K. Jayaraman ◽  
Li-Peng Choo ◽  
Shayan Kiumarsi

Consumers spend more time shopping and expect value-added options like backgroundmelodious songs, ample car parking, good ambience, prayer halls and rest rooms. The mainconcern is whether these facilities prolong consumers stay in the store and increase businesssales. This research article is about the relationship between the background music tempo andthe duration of consumers’ stay in the stores. Data from 177 respondents were received andanalyzed. The results show that the tempo of music is significantly affecting the emotionalstate of the consumers; fast tempo music increasing the pleasure and arousal levels. Slowtempo music has consumers stay longer in restaurants and supermarkets. However, the tempoof music does not play a significant role in manipulating the duration consumers spend in abook store and apparel shop.Keywords: Background Music; Arousal; Consumer Behavior; Shopping Experience; Stimulus-Organism-Response (S-O-R) Model.


2019 ◽  
Vol 21 (3) ◽  
pp. 264-279 ◽  
Author(s):  
Felix Dominik Weber ◽  
Reinhard Schütte

PurposeIn the most abstract way, artificial intelligence (AI) allows human work to be shifted toward technological systems that are currently not fully capable. Following this, the domain of retail can be sketched as a natural fit for the application of AI tools, which are known for their high proportion of human work and concurrent low profit margins. This paper aims to explore the current dissemination of the application of AI within the industry. The value-added core tasks of retail companies are examined to determine the possible utilization and the market adoption within the globally largest retail companies is given.Design/methodology/approachThe paper uses two different approaches to identify the scientific state-of-the-art: a search on the major scientific databases and an empirical study of the ten largest international retail companies and their adoption of AI technologies in the domains of wholesale and retail.FindingsThe application within the different value-added core tasks varies greatly depending on the area. In summary, there are numerous possible applications in all areas. Especially, in areas where future forecasts are needed within the task areas (such as marketing or replenishment), the use of AI, today, is both scientifically and practically highly developed. In contrast, the market adoption of AI is highly variable. The pioneers have integrated extensive applications into everyday business, while the challengers are investing heavily in new initiatives. Some others, however, show neither active use nor any effort to adopt such technology.Originality/valueTo the best of the author’s knowledge, this is one of the first research contributions to analyze the areas of application and the impact of AI structured along the value-added core processes of retail companies.


2011 ◽  
Vol 10 (01) ◽  
pp. 11-21 ◽  
Author(s):  
Samuel Kai Wah Chu ◽  
Kin Hang Chan ◽  
Ka Yin Yu ◽  
Hing Tai Ng ◽  
Wai Kwan Wong

This empirical study examines the intellectual capital (IC) performance of Hong Kong companies and its association with business performance. Data were collected from constituent companies of the Hang Seng Index listed on the Hong Kong Stock Exchange (2005–2008). An IC measurement, Value Added Intellectual Coefficient (VAICTM), was utilised to evaluate the IC investment of the companies. Four accounting ratios: market-to-book value (MB), return on assets (ROA), asset turnover (ATO) and return on equity (ROE) were used as the indicators of business performance. Regression analyses were conducted to test the ability of IC and its components in order to explain the variance in business performance measures. No conclusive evidence was found to support the associations between VAICTM as an aggregate measure and the four financial indicators. However, components of VAICTM were found to predict a substantial variance in business performance. Capital Employed Efficiency (CEE) was found to be a key factor in predicting business financial performance. Structural Capital Efficiency (SCE) was found to have a significant effect on businesses' market valuation, as measured by MB, and on profitability, as measured by ROE. Negative correlations were found between Human Capital Efficiency (HCE) and the financial indicators. The findings indicate a gap between the traditional accounting perspective and the value creation perspective, which is central to the VAICTM methodology in measuring IC. It is believed that the findings of this research provide insights for business stakeholders of Hong Kong companies in utilising IC, particularly the noted impact of structural capital. While our findings indicate the importance of IC for corporations, as shown by the significant effect of SCE on ROE, physical and financial assets may still be considered as the key resources in delivering business success.


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