Vincent K. Chong, Gary S. Monroe, Isabel Z. Wang and Feida (Frank) Zhang
This study examines the effect of employees' perceptions of political connections on performance measurement systems (PMS) design choice and firm performance. In addition, this…
Abstract
This study examines the effect of employees' perceptions of political connections on performance measurement systems (PMS) design choice and firm performance. In addition, this study explores the moderating effect of social networking, a very common and widely used factor by domestic and foreign multinational firms operating in China, and its joint effect with political connections or PMS design choice on firm performance. We collected survey responses from a sample of 110 managers from manufacturing firms in China. Our results reveal that highly politically connected managers use nonfinancial measures, leading to improved firm performance. Our results suggest that social networking interacts significantly with political connections, and nonfinancial and financial measures on firm performance. The theoretical and practical implications of our findings are discussed.
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Kam C. Chan, Chih-Hsiang Chang, Jamie Y. Tong and Feida (Frank) Zhang
The purpose of this paper is to conduct an assessment of the research productivity of the accounting and finance community in UK higher education institutions (HEIs) during…
Abstract
Purpose
The purpose of this paper is to conduct an assessment of the research productivity of the accounting and finance community in UK higher education institutions (HEIs) during 1991-2010 using 44 high-quality accounting and finance journals.
Design/methodology/approach
The authors follow Chan et al. (2011) to use their 22 finance journals. For accounting journals, the paper includes a set of 24 accounting journals that were used in a global accounting ranking study by Chan et al. (2007). The paper uses the number of coauthors (n) and coaffiliations (M) to derive the weighted articles as the measurement metric.
Findings
In general, the research output in terms of weighted articles steadily increases during the 20-year period. The University of Manchester, London School of Economics, and London Business School are the top-three HEIs using 44 accounting and finance journals for the full sample. The authors also find that it is a challenge to publish multiple articles. If an author is able to manage five total appearances, he/she is in the top 16 percent among the 1,447 UK authors. Furthermore, the paper finds that many highly productive authors are able to move to different jobs during the 20-year period.
Research limitations/implications
The assessment of research productivity is, unavoidably, based on a set of selected accounting and finance journals. Hence, no matter what journal screening criteria the paper uses, there is always a subjective element in the process. If other journals or more/less journals were to be included in a similar study, different results may emerge. As a way to extend the value of the research, it would be interesting to obtain broader institutional knowledge, such as the tenure requirements of HEIs in UK, and information on the institutions where faculty members obtained their doctoral degrees, so that the authors can better evaluate the research productivity among accounting and finance community in the UK.
Originality/value
The paper conducts an assessment of the research productivity of accounting and finance community in UK HEIs during 1991-2010 using 44 high-quality accounting and finance journals. The study fills the gap of the extant literature to compliment the assessment of the UK accounting and finance departments in RAEs.
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Carlos Renato Bueno, Juliano Endrigo Sordan, Pedro Carlos Oprime, Damaris Chieregato Vicentin and Giovanni Cláudio Pinto Condé
This study aims to analyze the performance of quality indices to continuously validate a predictive model focused on the control chart classification.
Abstract
Purpose
This study aims to analyze the performance of quality indices to continuously validate a predictive model focused on the control chart classification.
Design/methodology/approach
The research method used analytical statistical methods to propose a classification model. The project science research concepts were integrated with the statistical process monitoring (SPM) concepts using the modeling methods applied in the data science (DS) area. For the integration development, SPM Phases I and II were associated, generating models with a structured data analysis process, creating a continuous validation approach.
Findings
Validation was performed by simulation and analytical techniques applied to the Cohen’s Kappa index, supported by voluntary comparisons in the Matthews correlation coefficient (MCC) and the Youden index, generating prescriptive criteria for the classification. Kappa-based control charts performed well for m = 5 sample amounts and n = 500 sizes when Pe is less than 0.8. The simulations also showed that Kappa control requires fewer samples than the other indices studied.
Originality/value
The main contributions of this study to both theory and practitioners is summarized as follows: (1) it proposes DS and SPM integration; (2) it develops a tool for continuous predictive classification models validation; (3) it compares different indices for model quality, indicating their advantages and disadvantages; (4) it defines sampling criteria and procedure for SPM application considering the technique’s Phases I and II and (5) the validated approach serves as a basis for various analyses, enabling an objective comparison among all alternative designs.