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Turvey (2007, Physica A) introduced a scaled variance ratio procedure for testing the random walk hypothesis (RWH) for financial time series by estimating Hurst coefficients for a fractional Brownian motion model of asset prices. The purpose of this paper is to extend his work by making the estimation procedure robust to heteroskedasticity and by addressing the multiple hypothesis testing problem.

Unbiased, heteroskedasticity consistent, variance ratio estimates are calculated for end of day price data for eight time lags over 12 agricultural commodity futures (front month) and 40 US equities from 2000-2014. A bootstrapped stepdown procedure is used to obtain appropriate statistical confidence for the multiplicity of hypothesis tests. The variance ratio approach is compared against regression-based testing for fractionality.

Failing to account for bias, heteroskedasticity, and multiplicity of testing can lead to large numbers of erroneous rejections of the null hypothesis of efficient markets following an independent random walk. Even with these adjustments, a few futures contracts significantly violate independence for short lags at the 99 percent level, and a number of equities/lags violate independence at the 95 percent level. When testing at the asset level, futures prices are found not to contain fractional properties, while some equities do.

Only a subsample of futures and equities, and only a limited number of lags, are evaluated. It is possible that multiplicity adjustments for larger numbers of tests would result in fewer rejections of independence.

This paper provides empirical evidence that violations of the RWH for financial time series are likely to exist, but are perhaps less common than previously thought.

The introductory chapter includes how to design-in good practices in theory, data collection procedures, analysis, and interpretations to avoid these bad practices. Given that bad practices in research are ingrained in the career training of scholars in sub-disciplines of business/management (e.g., through reading articles exhibiting bad practices usually without discussions of the severe weaknesses in these studies and by research courses stressing the use of regression analysis and structural equation modeling), this editorial is likely to have little impact. However, scholars and executives supporting good practices should not lose hope. The relevant literature includes a few brilliant contributions that can serve as beacons for eliminating the current pervasive bad practices and for performing highly competent research.

The purpose of this paper is to consider the concepts of individual and complete statistical power used for multiple testing and shows their relevance for determining the number of statistical tests to perform when assessing non-response bias.

A statistical power analysis of 55 survey-based research papers published in three prestigious logistics journals (International Journal of Physical Distribution and Logistics Management, Journal of Business Logistics, Transportation Journal) over the last decade was conducted.

Results show that some of the low complete power levels encountered could have been avoided if fewer tests had been used in the assessment of non-response bias.

The research offers important recommendations to scholars engaged in survey research as they assess the effects of non-respondents on research findings. By following the recommended strategies for testing non-response bias, researchers can improve the statistical power of their findings.

The purpose of this paper is to investigate the simultaneous effect of attitude, subjective norm, perceived behavioral control (PBC), perceived value, and image on public transport passengers’ intention to reuse.

The empirical data were collected through survey. The respondents of the survey are 293 public transport passengers in Tangerang, Indonesia. Multiple regressions analysis was performed to test the conceptual model and the proposed hypotheses.

The findings showed that attitude, subjective norm, and image influence public transport passengers’ intention to reuse. However, this research also found that perceived value and PBC does not influence public transport passengers’ intention to reuse significantly.

The survey was only conducted at one area in Indonesia. In addition, convenience sampling method was employed. These conditions may cause that the research results cannot be generalized to the other contexts. Therefore, replication research is needed to test the stability of the findings in the other contexts.

Public transport service managers need to pay attention to attitude, subjective norm, and image in order to ensure public transport passengers’ intention to reuse public transport services.

This study is believed to be the first to develop and test public transport passengers’ intention to reuse model that integrated theory of planned behavior with perceived value and image.

This study aims to obtain an empirical evidence about the effect of good corporate governance on tax avoidance which becomes a proxy of current ETR (Effective Tax Rate). The samples of this study were 120 manufacturing companies listed in Indonesian Stock Exchange in 2010 – 2013. The hypothesis testing used multiple regression analysis. The result of this study show that audit committee has a positive effect on tax avoidance in partial but the executive compensation, executive character, company size, institutional ownership, boards of commisioners' proportion, audit committee and audit quality have simultaneous effect to define tax avoidance.

The purpose of this research is the exploration of online complainants' revenge based on their consumer-brand relationship strength and received webcare. The authors introduce inter-failures (i.e. the perceived number of earlier independent service failures that a customer has experienced with the same brand involved in the current service failure) as the central frame condition.

To test our hypotheses, both a scenario-based online experiment (n = 316) and an online survey (n = 492) were conducted.

With an increasing number of inter-failures, online complainants with a high-relationship strength move from the “love is blind” effect (no inter-failures) to the “love becomes hate” effect (multiple inter-failures), when they ultimately become more revengeful than their low-relationship strength counterparts. In addition, the authors show that in the case of no or few inter-failures, accommodative webcare has a lasting positive effect over no/defensive webcare for both low- and high-relationship complainants. More importantly, however, when consumers have experienced multiple inter-failures, accommodative webcare becomes ineffective (for low-relationship complainants) or boomerangs by cultivating revenge towards the brand (among high-relationship complainants), but not strategic avoidance.

The findings have pronounced implications for the literature on customer–brand relationships following service failures and the literature, which predominantly emphasizes the unconditionally positive effects of accommodative webcare.

This study is the first that simultaneously considers the prior customer–brand relationship, inter-failures and webcare to explain online complainants' revenge.

Chapter 16 is an introduction to systems thinking and analyzing the system dynamics of relationships within an organization or between organizations. Systems thinking builds on the propositions that (1) all variables or conditions have both dependent and independent relationships, (2) lag effects occur in relationships, (3) feedback relationships occur (e.g., A→B→C→A), and (4) seemingly minor relationships (i.e., “hidden demons”) have huge influence in causing a set of relationships (i.e., a system) to implode or explode. The propositions of building and testing a set of relationships apply in many contexts; this chapter examines systems thinking and system dynamics in one context as an introduction to this stream of case study research. Hall (1976) provides details of an advanced application of systems dynamics research – do not be fooled by the date of the study; Hall (1976) is an exceptional up-to-date case research study using system dynamics modeling. This chapter describes the issues and criticisms concerning golf, tourism, and the environment and considers how golf–tourism–environment relationships might achieve economic well-being for a region while avoiding vicious cycles of destruction to local environments and the quality of life of local residents. The examination proposes the use of systems thinking, cause mapping, and system dynamics modeling and simulations of golf, tourism, and environmental relationships to help achieve workable solutions agreeable to all stakeholders. Sustainable relationships that include golf, tourism, and environmental objectives require crafting government policies via stakeholder participation of all parties that such relationships affect – recognizing and enabling this requirement needs to be done explicitly – to reduce conflicts among stakeholders and avoid system failures.

Null-hypothesis significance tests (NHST) are a very troublesome methodology that dominates the quantitative empirical research in strategy and management. Inherent limitations and inappropriate applications of NHST impede the accumulation of knowledge and fill academic journals with meaningless “findings,” and they corrode researchers' motivation and ethics. Inherent limitations of NHST include the use of point null hypotheses, meaningless null hypotheses, and dichotomous truth criteria. Misunderstanding of NHST has often led to applications to inappropriate data and misinterpretation of results.

Researchers should move beyond the ritualistic and often inappropriate use of NHST. The chapter does not advocate a best way to do research, but suggests that researchers need to adapt their methods to reflect specific contexts and to use evaluation criteria that are meaningful for those contexts. Researchers need to explain the rationales that guided the selection of evaluation measures and they should avoid excessively complex models with many variables. The chapter also offers four more focused recommendations: (1) Compare proposed hypotheses with naïve hypotheses or the outcomes of alternative treatments. (2) Acknowledge the uncertainty that attends research findings by stating confidence limits for parameter estimates. (3) Show the substantive relevance of findings by reporting effect sizes – preferably with confidence limits. (4) Use statistical methods that are robust against deviations from assumptions about population distributions and the representativeness of samples.

The primary purpose of the research was to determine whether automotive manufacturers integrate multiple manufacturing initiatives and whether performance measures were impacted directly by these initiatives.

A mail survey questionnaire was used to gather data about the attitudinal attributes associated with implementing multiple manufacturing initiatives (i.e. ISO 9001, ISO 14001, lean manufacturing) and changes in key performance measures, both financial and nonfinancial. Descriptive statistics were utilized to gain a better understanding of the level of implementation of specific initiatives. Different forms of regression analysis were used to try to locate a statistically significant predictive model.

Two surveys of automotive suppliers were conducted during early summer 2001 and 2002 to gather information about multiple initiatives, customer mandates, and performance measurement. The results indicate that suppliers are not integrating the initiatives or linking them to financial and/or nonfinancial performance measurements. It was intended to develop a predictive model linking the implementation of multiple manufacturing initiatives and the impact on changing in performance measures. No statistically significant model was discovered. However, and not surprisingly, the level of implementation of different initiatives varies from one organization to another.

The size of the sample could pose a limitation in terms of generalizabiity. Also, this study was applied to specifically to the automotive supply parts industry and it could be applicable to other manufacturing supply chains.

Automotive industry suppliers have been faced with multiple, mandated requirements from the original equipment manufacturers. Continuing pressures to reduce price, improve quality, while producing an environmental friendly product using lean manufacturing practices has placed a financial strain on suppliers operating with thin profit margins. Are these initiatives being integrated into the overall business strategy and what impact are they having on performance measures? Based on the research, it did not appear to be well integrated. Additionally, a comparative analysis was conducted to note differences between senior management and middle management/professional staff. It was not surprising to find that senior management has higher expectations and opinions regarding implementation levels and performance.

The information in this study is particularly useful to manufacturers or others implementing standards or methodologies and to understand whether there is a direct impact on performance measurements.

The purpose of this paper is to analyze the dynamics of the triple helix model in less favoured regions, examining the role of three spheres: universities, firms, and government. The paper identifies profiles of behavior in terms of triple helix model performance from the firm's perspective and recognizes key factors for successful innovation dynamics in a less favored region of Portugal.

A brief bibliographic revision regarding development of the triple helix model in the innovation process is followed by a description of the role of the helixes and the presentation of a model, after which the hypotheses are defined for testing. The methodology consists of a survey involving companies in a less favored region of Portugal and the application of multivariate statistical analysis “k‐means clusters” to detect behavioral patterns in terms of performance and dynamics of the triple helix model from the firm's viewpoint. In order to verify the hypotheses, tests of multiple average differences are used to assess the unique characteristics of each cluster and the independent test of Chi‐square.

The results point to the existence of a positive relationship between the dynamics of the triple helix model in terms of different types and objectives to innovate, namely, in regards to introducing new products as well as ecological innovation and their efforts to improve communications relative to the obstacles to innovate – explicitly, the lack of information and geographical location, the companies' innovation performance, and the level of cooperation and interaction with the university producing benefits for them in obtaining additional financial resources and prestige for the researcher, as well as by obtaining information for the education process.

The paper contributes to a greater theoretical understanding of the variables influencing implementation of the triple helix model in less favoured regions. It reveals conditions associated with a more active and proactive stance and consequently better innovation dynamics and regional attractiveness.