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Control charts are designed to be effective in detecting a shift in the distribution of a process. Typically, these charts assume that the data for these processes follow an approximately normal distribution or some known distribution. However, if a data-generating process has a large proportion of zeros, that is, the data is intermittent, then traditional control charts may not adequately monitor these processes. The purpose of this study is to examine proposed control chart methods designed for monitoring a process with intermittent data to determine if they have a sufficiently small percentage of false out-of-control signals. Forecasting techniques for slow-moving/intermittent product demand have been extensively explored as intermittent data is common to operational management applications (Syntetos & Boylan, 2001, 2005, 2011; Willemain, Smart, & Schwarz, 2004). Extensions and modifications of traditional forecasting models have been proposed to model intermittent or slow-moving demand, including the associated trends, correlated demand, seasonality and other characteristics (Altay, Litteral, & Rudisill, 2012). Croston’s (1972) method and its adaptations have been among the principal procedures used in these applications. This paper proposes adapting Croston’s methodology to design control charts, similar to Exponentially Weighted Moving Average (EWMA) control charts, to be effective in monitoring processes with intermittent data. A simulation study is conducted to assess the performance of these proposed control charts by evaluating their Average Run Lengths (ARLs), or equivalently, their percent of false positive signals.

This study seeks to find an interactive effect between ethical leadership (EL) and corporate governance (CG) variables and investigate whether they would affect employee organizational citizenship behavior (EOCB) in a Malaysian organizational setting. The collected data from the 300 accounting/finance department employees were analyzed using Statistical Package for Social Sciences (SPSS) and Partial Least Square–Structural Equation Modeling (PLS-SEM; SmartPLS 3.0). Several primary results confirmed a coherent significant relationship between EL and ethical climate (EC), EL and EOCB, EL and CG, and CG and organizational success. Theoretically, it implies a more enhanced EOCB literature on how it can be infused in an organization. It also offers valuable knowledge by providing organizations with several insights concerning the improvement of EOCB, enabling the organization to achieve its desired success and, more importantly, how the findings could contribute directly and indirectly to emerging markets in terms of their industrial and financial performance.

The current longitudinal study investigated the within- and between-person variance in work-to-family conflict and family-to-work conflict among working mothers over time. It also examined the effects of a nonstandard work schedule and relationship quality on work-to-family conflict and family-to-work conflict using bioecological theory. Results of multilevel modeling analyses showed that there was significant within- and between-person variance in work-to-family conflict and family-to-work conflict. The linear and quadratic terms were significantly related to family-to-work conflict, whereas the quadratic term was significantly associated with work-to-family conflict. There was also a positive relationship between a nonstandard work schedule and work-to-family conflict, whereas relationship quality was negatively associated with family-to-work conflict. Future studies should consider diversity among working mothers to adequately predict work–family conflict. The current study provides important implications for employers to consider, concerning within-and between-person differences among working mothers, which could in turn allow for accommodations and help to decrease work–family conflict.

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.