Agglomeration Economies and Productivity Growth in Manufacturing Industry: Empirical Evidence from Indonesia

This study examines the effect of agglomeration economies on productivity growth in Indonesian manufacturing industries during the first decade of this century. Productivity growth is measured at the firm level using the Färe‐Primont Productivity Index. Each firm's productivity growth is then regressed against a set of firm and industry characteristics, including three measures of agglomeration representing the effects of specialisation, diversity and competition. The results show evidence of a positive specialisation effect and a negative diversity effect for aggregate manufacturing and sub‐sectors. Furthermore, there are mixed effects across industries, suggesting that Porter's competition externalities stimulate firm productivity growth under some conditions but not others.     

The effects of corporate governance and audit and non-audit fees on IPO Value

This paper examines the effects of non-executive board members, audit committee composition and financial expertise, and fees paid to audit firms on the value of 375 UK initial public offerings (IPOs). Empirical findings show that underpricing decreases in audit fees whereas it increases in non-audit fees. A higher proportion of non-executive directors on the firm’s board and audit committees with a higher proportion of non-executive directors and financial accounting expertise of their members positively moderate the inter-relationships between underpricing and both audit and non-audit fees paid by companies going through an IPO. Further investigations using the adjusted price-to-book value as a proxy for firm value at IPO confirm our main findings that internal governance mechanisms may complement services provided by the auditors in terms of generating higher valuations. Controlling for the simultaneous determination of audit and non-audit fees, our results remain consistent.     

Does R&D spur productivity growth in Australia’s broadacre agriculture? A semi-parametric smooth coefficient approach

This article analyses the role of research and development (R&D) in Australia’s broadacre farming by using the semi-parametric smooth coefficient model. While the conventional production function approach only captures the direct effects of R&D, this methodology captures both the direct impact of a change in R&D on output and the indirect impact through changes in efficiency of use of factor inputs in the production process. Moreover, technical inefficiency is introduced in the model allowing it as a function of R&D. Using a unique state-level dataset covering the period 1995–2007, this empirical study finds that once both the direct and indirect effects are taken into consideration, R&D investments significantly increase outputs. The results also show that there are substantial variations in the effects of R&D on output across the state-level average farm through technology parameters as well as through technical inefficiency. Such variations need to be taken into account when designing policies for investing public R&D in agriculture.     

Listening to the patient voice: using a sentic computing model to evaluate physicians’ healthcare service quality for strategic planning in hospitals

Online physician reviews (OPRs), also known as electronic word of mouth, have become the primary source of information for patients while making health consultation decisions. However, different techniques to analyze these reviews by machines have not been frequently applied yet in this domain. In this study, a novel method for opinion mining is being proposed to fill the existing research gap, that is, a hybrid approach to sentic computing. This approach integrates artificial intelligence and semantic web techniques to implicitly analyze OPRs in order to evaluate patient perceptions of healthcare service quality. We develop our methodology by using the following three main tasks: (1) sentence-level topic spotting (a topic-analysis procedure) to extract major topics, (2) a sentic computing framework to perform concept-level sentiment analysis (polarity detection on the categorized sentences), and (3) root cause and strengths, weaknesses, opportunities, and threats (SWOT) analyses to identify SWOT for healthcare organizations. Analyses results of 47,499 OPRs from the UK-based website (Iwantgreatcare.org) show that the proposed hybrid approach has accurately classified concept words to their corresponding topics, and it has also outperformed the similar other methods of topic extraction in the healthcare domain. The results also indicate that the proposed approach can better contribute to the overall performance analyses for healthcare organizations, which could help practitioners in improving service-quality measures based on the real voices of patients. The proposed model also provides a theoretical basis for formulating quality measures for the healthcare sector.