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A large literature over several decades reveals both extensive concern with the question of time-varying betas and an emerging consensus that betas are in fact time-varying, leading to the prominence of the conditional CAPM. Set against that background, we assess the dynamics in realized betas, vis-à-vis the dynamics in the underlying realized market variance and individual equity covariances with the market. Working in the recently popularized framework of realized volatility, we are led to a framework of nonlinear fractional cointegration: although realized variances and covariances are very highly persistent and well approximated as fractionally integrated, realized betas, which are simple nonlinear functions of those realized variances and covariances, are less persistent and arguably best modeled as stationary I(0) processes. We conclude by drawing implications for asset pricing and portfolio management.

This research studies private information from extreme price movements or jumps. The authors calculate the private information using a reduced form model from the stochastic volatility jump process and use several statistical robustness tests as well as several frequencies to improve our consistency. This study reveals that private information is significant in explain the existence of jumps in capital markets in Southeast Asia, whereas macroeconomic events cannot explain them. The authors determine empirically that private information in Malaysia, Singapore, Thailand, and Indonesia are not persistent and its value gradually decreases when we use the lower frequency. Based on the Fama–Macbeth regression, this study shows that private information in the capital market has a strong positive relationship with individual returns in Indonesia’s capital market and Thailand’s capital market for all frequencies.

This paper gives a selective review on some recent developments of nonparametric methods in both continuous and discrete time finance, particularly in the areas of nonparametric estimation and testing of diffusion processes, nonparametric testing of parametric diffusion models, nonparametric pricing of derivatives, nonparametric estimation and hypothesis testing for nonlinear pricing kernel, and nonparametric predictability of asset returns. For each financial context, the paper discusses the suitable statistical concepts, models, and modeling procedures, as well as some of their applications to financial data. Their relative strengths and weaknesses are discussed. Much theoretical and empirical research is needed in this area, and more importantly, the paper points to several aspects that deserve further investigation.

Differential search algorithm (DSA) is a new optimization, meta-heuristic algorithm. It simulates the Brownian-like, random-walk movement of an organism by migrating to a better position. The purpose of this paper is to analyze the performance analysis of DSA into two key parts: six random number generators (RNGs) and Benchmark functions (BMF) from IEEE World Congress on Evolutionary Computation (CEC, 2015). Noting that this study took problem dimensionality and maximum function evaluation (MFE) into account, various configurations were executed to check the parameters’ influence. Shifted rotated Rastrigin’s functions provided the best outcomes for the majority of RNGs, and minimum dimensionality offered the best average. Among almost all BMFs studied, Weibull and Beta RNGs concluded with the best and worst averages, respectively. In sum, 50,000 MFE provided the best results with almost RNGs and BMFs.

DSA was tested under six randomizers (Bernoulli, Beta, Binomial, Chisquare, Rayleigh, Weibull), two unimodal functions (rotated high conditioned elliptic function, rotated cigar function), three simple multi-modal functions (shifted rotated Ackley’s, shifted rotated Rastrigin’s, shifted rotated Schwefel’s functions) and three hybrid Functions (Hybrid Function 1 (n=3), Hybrid Function 2 (n=4,and Hybrid Function 3 (n=5)) at four problem dimensionalities (10D, 30D, 50D and 100D). According to the protocol of the CEC (2015) testbed, the stopping criteria are the MFEs, which are set to 10,000, 50,000 and 100,000. All algorithms mentioned were implemented on PC running Windows 8.1, i5 CPU at 1.60 GHz, 2.29 GHz and a 64-bit operating system.

The authors concluded the results based on RNGs as follows: F3 gave the best average results with Bernoulli, whereas F4 resulted in the best outcomes with all other RNGs; minimum and maximum dimensionality offered the best and worst averages, respectively; and Bernoulli and Binomial RNGs retained the best and worst averages, respectively, when all other parameters were fixed. In addition, the authors’ results concluded, based on BMFs: Weibull and Beta RNGs produced the best and worst averages with most BMFs; shifted and rotated Rastrigin’s function and Hybrid Function 2 gave rise to the best and worst averages. In both parts, 50,000 MFEs offered the best average results with most RNGs and BMFs.

Being aware of the advantages and drawbacks of DS enlarges knowledge about the class in which differential evolution belongs. Application of that knowledge, to specific problems, ensures that the possible improvements are not randomly applied. Strengths and weaknesses influenced by the characteristics of the problem being solved (e.g. linearity, dimensionality) and by the internal approaches being used (e.g. stop criteria, parameter control settings, initialization procedure) are not studied in detail. In-depth study of performance under various conditions is a “must” if one desires to efficiently apply DS algorithms to help solve specific problems. In this work, all the functions were chosen from the 2015 IEEE World Congress on Evolutionary Computation (CEC, 2015).

This paper aims to identify the characteristics of enduring audience engagement through social media.

The approach is to examine recent examples of successful social media practices to identify common characteristics.

The most common characteristics of successful social media engagement include continuous beta, co-ownership, room for error and convenor-ship.

The author’s analogy of successful social media to the biophysical phenomenon of entrainment is an original insight into social engagement.

Due to the complexity of digital services, companies are increasingly forced to offer their services “in permanent beta”, requiring continuous fine-tuning and updating. Complexity makes it extremely difficult to predict when and where the next service disruption will occur. The authors examine what this means for performance measurement in digital service supply chains.

The authors use a mixed-method research design that combines a longitudinal case study of a European digital TV service provider and a system dynamics simulation analysis of that service provider's digital service supply chain.

With increased levels of complexity, traditional performance measurement methods, focused on detection of software bugs before release, become fragile or futile. The authors find that monitoring the performance of the service after release, with fast mitigation when service incidents are discovered, appears to be superior. This involves organizational change when traditional methods, like quality assurance, become less important.

The performance of digital services needs to be monitored by combining automated data collection about the status of the service with data interpretation using human expertise. Investing in human expertise is equally important as investing in automated processes.

The authors draw on unique empirical data collected from a digital service provider's struggle with performance measurement of its service over a period of nine years. The authors use simulations to show the impact of complexity on staff allocation.

This paper aims to analyze the factors that influence the quality of internal audits in Brazilian federal educational institutions.

The study consisted of a survey whose target participants were members of the internal audits and members of the senior management of Brazilian Federal Educational Institutions. The analyses included descriptive statistics of the sample, exploratory factor analysis and multiple regression analysis.

The results showed that the internal audit functions, continuous improvement practices and relationship between internal and external auditors as factors had a positive impact on the internal audit quality dependent variable. The internal audit functions and continuous improvement practices as factors influenced both models that were created (audit members and senior management), whereas the relationship between internal and external auditors was only relevant to senior management. Organizational support and internal audit autonomy, on the other hand, were not statistically significant.

Considering the recent Brazilian research on internal auditing in Educational Institutions, this study differs from others in that it covered all the Universities (63), Federal Institutes (38), Federal Centers of Technological Education (2) and Colégio Pedro II. Another relevant issue refers to the target audience, addressing both the members of the internal audits (supply side) and the Senior Management (one of the main parties impacted by the work of the internal audits).

The main objective of this study was to examine academic staff's perceptions of the characteristics of a learning organization within higher education: in this instance, the International Islamic University Malaysia (IIUM). The study also examined the relationship between the characteristics of a learning organization and satisfaction with performance in teaching and research activities.

A survey method was used in a sample of 400 academicians with a return rate of 214 (53.5 per cent). Watkins and Marsick's and Marsick and Watkins's learning organization questionnaire was used to measure the characteristics of the learning organization and to collect data for the study.

The main results showed that the academic staff indicated moderate levels of the characteristics of a learning organization and satisfaction with performance. The results also showed that there were positive and significant relationships between dimensions of the learning organization and satisfaction with performance activities in teaching and research. Furthermore, dimensions of the learning organization accounted for small but significant variance of satisfaction with both teaching and research performance activities.

This study contributes empirical findings on learning organization in a higher learning institution, a research area in which there is a scarcity of empirical studies.

Using a qualitative methodology, the present research attempts to understand members’ perceptions of empowerment in two New Zealand organizations that have undergone various reforms in the workplace. In a departure from the literature, our study reveals the context‐specific nature of empowerment and offers probable reasons for the lack of a unified (or universal) definition. From our case data, we also identify several factors that either facilitate or inhibit the empowerment process, and that have significant implications for organizations seeking to empower their employees.

There is considerable confusion surrounding the applied role and business value of TQM. Anecdotal evidence and empirical studies in the literature suggest considerable variability in the performance of TQM. The purpose of the paper is to test the strength of the relationship between quality management practice and two key operational performance measures: productivity improvement and customer satisfaction.

A large database consisting of 962 responses from Australian manufacturing firms and 379 responses from New Zealand manufacturing firms is used to test the hypotheses.

The major finding of the paper is that multiple quality management practices when implemented simultaneously have a significant and positive effect on productivity improvement and customer satisfaction.

The results presented in this paper are drawn from one industry at one point in time. Generalising the results to other industries should be done with caution. This study, therefore, aims to motivate further research on the link between quality strategies and organisational performance.

The main implication that emerges from the paper is that managers in manufacturing firms should place more emphasis on “soft” quality management practices (e.g. unity of purpose/elimination of barriers between individuals and departments) and less emphasis on “hard” practices (e.g. process control).

The paper fulfils an identified need on the value of quality practice and offers practical implications to managers and stimulates further research on the relationship between quality practice and operational performance in non‐manufacturing industries.