HRM systems, internal marketing and performance in Indian call centres:full research report ESRC end of award report, RES-000-22-1876

Considering the rapid growth of call centres (CCs) in India, its implications for businesses in the UK and a scarcity of research on human resource management (HRM) related issues in Indian CCs, this research has two main aims. First, to highlight the nature of HRM systems relevant to Indian call centres. Second, to understand the significance of internal marketing (IM) in influencing the frontline employees’ job-related attitudes and performance. Rewards being an important component of IM, the relationships between different types of rewards as part of an IM strategy, attitudes and performance of employees in Indian CCs will also be examined. Further, the research will investigate which type of commitment mediates the link between rewards and performance and why. The data collection will be via two phases. The first phase would involve a series of in-depth interviews with both the managers and employees to understand the functioning of CCs, and development of suitable HRM systems for the Indian context. The second phase would involve data collection through questionnaires distributed to the frontline employees and supervisors to examine the relationships among IM, employee attitudes and performance. Such an investigation is expected to contribute to development of better theory and practice.

Cost economies, efficiency and productivity growth in the Chinese banking industry:evidence from a quarterly panel dataset

This article examines cost economies, productivity growth and cost efficiency of the Chinese banks using a unique panel dataset that identifies banks' four outputs and four input prices over the period of 1995-2001. By assessing the appropriateness of model specification, and making use of alternative methodologies in evaluating the performance of banks, we find that the joint-stock commercial banks outperform state-owned commercial banks in productivity growth and cost efficiency. Under the variable cost assumption, Chinese banks display economies of scale, with state-owned commercial banks enjoying cost advantages over the joint-stock commercial banks. Consequently, our results highlight the ownership advantage of these two types of banks and generally support the ongoing banking reform and transformation that is currently taking place in China.

Red capitalists:political connections and firm performance in China

Using a unique firm level data, this paper analyses the role of political connections in the post-entry performance of private start-up companies in China. It documents robust evidence that political affiliation enhances firms' survival and growth prospects. But interestingly politically neutral start-ups enjoy faster productivity improvements conditional on survival. In addition, the benefits of political connections are largely confined to firms associated with local or top level governments, and they are more pronounced in capital-intensive industries. We conclude that the close association between the state and a segment of the business community is leading to sub-optimal resource allocation in the economy by interfering with the process of market selection.

How transition paths differ:enterprise performance in Russia and China

We use enterprise survey data to analyse and contrast the determinants of enterprise performance in China and Russia. We find that in China, enterprise growth and efficiency is associated with rapid increases in factor inputs, and with ownership to a lesser extent, but not greatly correlated with industry-specific or institutional factors. However, in Russia, enterprise growth is not associated with improvements in factor quantity (except for labor) or quality. The main determinants of company performance are instead demand and institutional factors at a regional level. The findings are robust across a variety of specifications.

The innovation value chain and export performance:a study of Taiwanese manufacturing industries

This thesis involves the secondary data of 1806 innovative manufacturing firms derived from the database of 2nd Taiwanese Innovation Survey. Three topics are researched. The first topic investigates the innovation value chain (IVC) in Taiwanese manufacturing firms. Previous IVC studies are all done in developed countries such as UK, Ireland, Northern Ireland and Switzerland, and it leaves the gap of those non-developed countries. The result shows the overall knowledge sourcing pattern of Taiwanese manufacturing firms presenting a complementary relationship which is consistent to the previous IVC studies. The main innovation input is still derived from internal R&D which suggests more utilisation of external knowledge may boost innovation outcome. Product innovation does enhance firm growth while process innovation reduces a firm’s productivity. The second topic uses the lens of IVC to investigate the difference of the innovation process from knowledge linkages to value added between high-tech and low- tech sectors. The findings indicate (1) there are significant differences in the IVC between high- and low-tech sectors, however these are defined; (2) how you define ‘sector’ matters i.e. the nature of the high-tech and low-tech differences varies depending on whether the technology definition is carried out at the industry or firm level; and (3) the high uncertainty of innovation cause the difficulty to predict firm performance especially for those firms with high intensity of innovation. The third topic investigates the innovation-exporting relationship and explores the determinants of export performance. Product innovation enhances export performance once a firm enters international markets while process innovation affects negatively on a firm’s likelihood of being an exporter. Furthermore, IP protection is found to affect directly export performance positively.

What can situated learning theory tell us about leading to develop organizational learning capabilities for entrepreneurial performance? lessons from a knowledge-intensive small firm

Although the role of strategic leadership in developing organizational learning capabilities has been examined to a certain extent, the specific behaviors and mechanisms through which these capabilities are developed have not been adequately understood. Paucity of research in this direction is even more conspicuous in a small firm/entrepreneurship context, which has been linked to innovation, economic growth, and employment generation. Reporting on an ethnographic study of a knowledge-intensive, growth-oriented small firm, this article addresses this gap in the literature by integrating strategic leadership and organizational learning theory in an entrepreneurship context. In this undertaking, situated learning theory is used as the major analytical lens, to shed light on how strategic leadership can build organizational learning capabilities that underpin entrepreneurial performance in small firms. Finally, implications for situated learning theory as an organizational learning perspective and leadership practice in an entrepreneurship context are submitted. © 2012 Wiley Periodicals, Inc.

HRM systems, internal marketing and performance in Indian call centres:non-technical summary (Research summary) ESRC end of award report, RES-000-22-1876. Swindon: ESRC

Considering the rapid growth of call centres (CCs) in India, its implications for businesses in the UK and a scarcity of research on human resource management (HRM) related issues in Indian CCs, this research has two main aims. First, to highlight the nature of HRM systems relevant to Indian call centres. Second, to understand the significance of internal marketing (IM) in influencing the frontline employees’ job-related attitudes and performance. Rewards being an important component of IM, the relationships between different types of rewards as part of an IM strategy, attitudes and performance of employees in Indian CCs will also be examined. Further, the research will investigate which type of commitment mediates the link between rewards and performance and why. The data collection will be via two phases. The first phase would involve a series of in-depth interviews with both the managers and employees to understand the functioning of CCs, and development of suitable HRM systems for the Indian context. The second phase would involve data collection through questionnaires distributed to the frontline employees and supervisors to examine the relationships among IM, employee attitudes and performance. Such an investigation is expected to contribute to development of better theory and practice.

Productivity change using growth accounting and frontier-based approaches:evidence from a Monte Carlo analysis

This study presents some quantitative evidence from a number of simulation experiments on the accuracy of the productivitygrowth estimates derived from growthaccounting (GA) and frontier-based methods (namely data envelopment analysis-, corrected ordinary least squares-, and stochastic frontier analysis-based malmquist indices) under various conditions. These include the presence of technical inefficiency, measurement error, misspecification of the production function (for the GA and parametric approaches) and increased input and price volatility from one period to the next. The study finds that the frontier-based methods usually outperform GA, but the overall performance varies by experiment. Parametric approaches generally perform best when there is no functional form misspecification, but their accuracy greatly diminishes otherwise. The results also show that the deterministic approaches perform adequately even under conditions of (modest) measurement error and when measurement error becomes larger, the accuracy of all approaches (including stochastic approaches) deteriorates rapidly, to the point that their estimates could be considered unreliable for policy purposes.

Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector

Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.

Trends, challenges and opportunities for performance engineering with modern business software

The author looks at trends in software and systems, and the current and likely implications of these trends on the discipline of performance engineering. In particular, he examines software complexity growth and its consequences for performance engineering for enhanced understanding, more efficient analysis and effective performance improvement. The pressures for adaptive and autonomous systems introduce further opportunities for performance innovation. The promise of aspect oriented software development technologies for assisting with some of these challenges is introduced.

Satisfaction as a predictor of future performance:a replication

Since the introduction of the Net Promoter concept there has been a vivid and ongoing debate among academics and practitioners about the performance of the Net Promoter Score (NPS) in comparison to other customer metrics, such as customer satisfaction, to predict company growth rates. We report results from a study using data from customers and firms in the Netherlands on the relationship between different satisfaction and loyalty metrics as well as the NPS with sales revenue growth, gross margins and net operating cash flows. We find that all metrics perform equally well in predicting current gross margins and current sales revenue growth and equally poor for predicting future sales growth and gross margins as well as current and future net cash flows. The NPS is neither superior nor inferior to other metrics. Taken together, our study suggests that the predictive capability of customer metrics, such as NPS, for future company growth rates is limited. © 2013 Elsevier B.V.

Small business performance:business, strategy and owner-manager characteristics

Purpose: This paper aims to contribute to the understanding of the factors that influence small to medium-sized enterprise (SME) performance and particularly, growth. Design/methodology/approach: This paper utilises an original data set of 360 SMEs employing 5-249 people to run logit regression models of employment growth, turnover growth and profitability. The models include characteristics of the businesses, the owner-managers and their strategies. Findings: The results suggest that size and age of enterprise dominate performance and are more important than strategy and the entrepreneurial characteristics of the owner. Having a business plan was also found to be important. Research limitations/implications: The results contribute to the development of theoretical and knowledge bases, as well as offering results that will be of interest to research and policy communities. The results are limited to a single survey, using cross-sectional data. Practical implications: The findings have a bearing on business growth strategy for policy makers. The results suggest that policy measures that promote the take-up of business plans and are targeted at younger, larger-sized businesses may have the greatest impact in terms of helping to facilitate business growth. Originality/value: A novel feature of the models is the incorporation of entrepreneurial traits and whether there were any collaborative joint venture arrangements. © Emerald Group Publishing Limited.

Cardiac dysfunction and cell damage across clinical stages of severity in growth-restricted fetuses

Objective - The purpose of this study was to assess cardiac function and cell damage in intrauterine growth-restricted (IUGR) fetuses across clinical Doppler stages of deterioration. Study Design - One hundred twenty appropriate-for-gestational-age and 81 IUGR fetuses were classified in stages 1/2/3 according umbilical artery present/absent/reversed end-diastolic blood flow, respectively. Cardiac function was assessed by modified-myocardial performance index, early-to-late diastolic filling ratios, cardiac output, and cord blood B-type natriuretic peptide; myocardial cell damage was assessed by heart fatty acid–binding protein, troponin-I, and high-sensitivity C-reactive protein. Results - Modified-myocardial performance index, blood B-type natriuretic peptide, and early-to-late diastolic filling ratios were increased in a stage-dependent manner in IUGR fetuses, compared with appropriate-for-gestational-age fetuses. Heart fatty acid–binding protein levels were higher in IUGR fetuses at stage 3, compared with control fetuses. Cardiac output, troponin-I, and high-sensitivity C-reactive protein did not increase in IUGR fetuses at any stage. Conclusion - IUGR fetuses showed signs of cardiac dysfunction from early stages. Cardiac dysfunction deteriorates further with the progression of fetal compromise, together with the appearance of biochemical signs of cell damage.

Productivity growth and efficiency measurements in fuzzy environments with an application to health care

Health care organizations must continuously improve their productivity to sustain long-term growth and profitability. Sustainable productivity performance is mostly assumed to be a natural outcome of successful health care management. Data envelopment analysis (DEA) is a popular mathematical programming method for comparing the inputs and outputs of a set of homogenous decision making units (DMUs) by evaluating their relative efficiency. The Malmquist productivity index (MPI) is widely used for productivity analysis by relying on constructing a best practice frontier and calculating the relative performance of a DMU for different time periods. The conventional DEA requires accurate and crisp data to calculate the MPI. However, the real-world data are often imprecise and vague. In this study, the authors propose a novel productivity measurement approach in fuzzy environments with MPI. An application of the proposed approach in health care is presented to demonstrate the simplicity and efficacy of the procedures and algorithms in a hospital efficiency study conducted for a State Office of Inspector General in the United States. © 2012, IGI Global.

The association between the use of IP by UK SMEs in 2001 and subsequent performance in 2002 to 2004

This report analyses the 2001 cohort of UK SMEs. The specific focus is on the link between IP activity in 2001 and subsequent performance (to 2004). The 2001 cohort contains 130,082 SMEs of which 3,123 were IP active (2.4%). Specifically, 1,872 SMEs had at least one UK trade mark publication; 697 had one or more Community trade mark registrations; 646 SMEs had one or more UK patents; and 443 had one or more EPO patent publications. The outcome and financial performance of the SMEs is analysed in various ways. Initially, we look at the determinants of survival to 2004. We then look at growth of assets and turnover for the period 2001 to 2004.