This paper aims to examine how Hong Kong universities have responded to a newly included assessment element of socio-economic impact in a government-implemented research…
Abstract
Purpose
This paper aims to examine how Hong Kong universities have responded to a newly included assessment element of socio-economic impact in a government-implemented research evaluation system – Research Assessment Exercise (RAE) 2020 – within the context of tightening audits and forceful knowledge economy objectives.
Design/methodology/approach
This paper reports an institutional case study of the institutional-level response to the RAE 2020 impact requirement at a top-ranked comprehensive university in Hong Kong. A qualitative inquiry approach was adopted. The data sources mainly include university documents related to the RAE 2020 socio-economic impact policy, interview data with nine RAE-eligible academics at the case university, documents on the RAE exercises issued by the University Grants Committee (UGC) and field notes taken during the RAE information sessions.
Findings
The institutionalisation process of the RAE socio-economic impact agenda could be considered as establishing an indicator-oriented reward and recognition regime for knowledge transfer and knowledge exchange (KT/KE). Overall, two major institutional strategies were identified in operating the RAE 2020 impact agenda at the case university: (1) launching various policy initiatives: driven by the RAE-defined socio-economic impact; (2) incorporating socio-economic impact into faculty evaluation: premised upon the 16 KT performance indicators laid down by the UGC.
Originality/value
This article adds to the theoretical debate on the local reproduction of the global in studies of neoliberalism in higher education by describing a Hong Kong case study, supported by empirical data, of an actual university's responses to the newly included impact requirement in RAE 2020. More specifically, this study reveals that (1) the policy for socio-economic impact might be designed in a neutral or even benevolent manner, but has taken on a neoliberal and managerial dimension in its actual implementation; and (2) the neoliberal discourse underpinning the university's operation can be accounted for and explicated by the local factors embedded in the specific academic environment.
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Danling Jiang, Liu Shuying, Feiyu Li and Hongquan Zhu
This paper intends to study how geographic heterogeneity in urban vibrancy, especially in human capital creation, helps explain persist firm valuation dispersion across cities in…
Abstract
Purpose
This paper intends to study how geographic heterogeneity in urban vibrancy, especially in human capital creation, helps explain persist firm valuation dispersion across cities in China.
Design/methodology/approach
This paper studies geographic differences in firm valuations of 1,023 listed companies headquartered in 35 major cities in China from 2001 to 2018. The authors estimate panel regressions of local firm Tobin's q on city fixed effects or city endowed attributes in human capital creation after controlling industry-year fixed effects as well as a set of firm and city time variant attributes.
Findings
The results show persistent, significant city-to-city differences in Tobin's q, especially among large, mature or high labor-intensive firms. To explain such geographic differences in firm valuations, the authors identify several factors of the endowed city competitive advantages in creating human capital that play important roles in explaining the persistent geographic firm valuation premia.
Originality/value
This paper provides the first systematic analysis of urban vibrancy in human capital supply in explaining persistent geographic firm valuation dispersion in China. The evidence suggests that city endowed comparative advantages in supplying human capital have created long-lasting, and growing, shareholder wealth by attracting and retaining talents and human resources in local firms.
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Silvanus Teneng Kiyang and Robert Van Zyl
The purpose of this work is to assess the influence of ambient noise on the performance of wireless sensor networks (WSNs) empirically and, based on these findings, develop a…
Abstract
Purpose
The purpose of this work is to assess the influence of ambient noise on the performance of wireless sensor networks (WSNs) empirically and, based on these findings, develop a mathematical tool to assist technicians to determine the maximum inter-node separation before deploying a new WSN.
Design/methodology/approach
A WSN test platform is set up in an electromagnetically shielded environment (RF chamber) to accurately control and quantify the ambient noise level. The test platform is subsequently placed in an operational laboratory to record network performance in typical unshielded spaces. Results from the RF chamber and the real-life environments are analysed.
Findings
A minimum signal-to-noise ratio (SNR) at which the network still functions was found to be of the order 30 dB. In the real-life scenarios (machines, telecommunications and computer laboratories), the measured SNR exceeded this minimum value by more than 20 dB. This is due to the low ambient industrial noise levels observed in the 2.4 GHz ISM band for typical environments found at academic institutions. It, therefore, suggests that WSNs are less prone to industrial interferences than anticipated.
Originality/value
A predictive mathematical tool is developed that can be used by technicians to determine the maximum inter-node separation before the WSN is deployed. The tool yields reliable results and promises to save installation time.
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While scheduling and transporting emergency materials in disasters, the emergency materials and delivery vehicles are arriving at the distributing center constantly. Meanwhile…
Abstract
Purpose
While scheduling and transporting emergency materials in disasters, the emergency materials and delivery vehicles are arriving at the distributing center constantly. Meanwhile, the information of the disaster reported to the government is updating continuously. Therefore, this paper aims to propose an approach to help the government make a transportation plan of vehicles in response to the disasters addressing the problem of material demand and vehicle amount continual alteration.
Design/methodology/approach
After elaborating the features and process of the emergency materials transportation, this paper proposes an emergency materials scheduling model in the case of material demand and vehicle amount continual alteration. To solve this model, the paper provides the vehicle transportation route allocation algorithm based on dynamic programming and the disaster area supply sequence self-learning algorithm based on ant colony optimization. Afterwards, the paper uses the model and the solution approach to computing the optimal transportation scheme of the food supply in Lushan earthquake in China.
Findings
The case study shows that the model and the solution approach proposed by this paper are valuable to make the emergency materials transportation scheme precise and efficient. The problem of material demand and vehicle amount changing continually during the process of the emergency materials transportation is solved promptly.
Originality/value
The model proposed by this paper improves the existing similar models in the following aspects: the model and the solution approach can not only solve the emergency materials transportation problem in the condition of varying demand and vehicle amount but also save much computing time; and the assumptions of this model are consistent with the actual situation of the emergency relief in disasters so that the model has a broad scope of application.