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This study aims to examine the impacts of board chairman characteristics on the decision to finance with debts.

Based on historical data from 173 active nonfinancial firms listed on Gulf Cooperation Council (GCC) Stock Exchange Markets during 2012–2019, this research uses ordinary least squares (OLS) and dynamic system-generalized methods of moments to test its hypotheses. The final dataset comprises 1,384 firm-year observations from 10 major nonfinancial industry classifications.

Results indicate a negative impact of board chairman ownership on the decision to finance with retained earnings (RE). Negative effects of the chairman and chief executive officer (CEO) from the same family on the decision to finance with RE, whereas positive effects of the chairman and CEO from the same family on the decision to finance with debts are observed. In addition, a negative effect of the chairman from a royal family on the decision to invest with debts is found.

Many board chairmen characteristics, such as age, gender, experience, education level, periodic change and ethnicity, are unaddressed. Financial decisions (FDs) are also limited to two decisions (internal financing with RE and external financing with debts).

Findings of this study provide an improved understanding of the role of chairman characteristics in FDs in GCC. Investors and lenders dealing with companies in GCC markets benefit from the authors' results because of the effects of chairman characteristics on FDs when making investment decisions in company stocks.

The study clarifies how each of the three board chairman characteristics (i.e. chairman ownership, chairman and CEO from the same family and the chairman from the royal family) affects FDs, especially the decisions to finance with debts and RE.

The aim of this paper is to explore the implementation of an integrated lean and ISO 14001 approach in meat industry for environmental performance and examine a proposed conceptual framework by capturing insights from lean and ISO 14001 experts in New Zealand (NZ).

Semi-structured interviews have been conducted with a group of consultants (lean and ISO 14001) to evaluate the suitability of an integrated lean and ISO 14001 approach in the meat industry for environmental performance. A conceptual framework from literature has guided this study leading to its further development based on the empirical evidence collected.

Findings have illustrated a synergistic positive impact of lean and ISO 14001 implementation as an integrated approach for sustaining environmental performance in the meat industry. A joint implementation program provides more clarity in aligning ISO 14001 operational procedures with lean tools and techniques for an enhanced environmental performance outcome.

The application of an integrated lean and ISO 14001 framework is proposed in this paper, which can help industry practitioners and academia in developing a joint implementation strategy and conducting future research.

To the best of the author’s knowledge, this study is the first to assess the effective implementation of lean and ISO 14001 as an integrated approach in the NZ meat industry.

This paper recommends a method entitled “SMED 4.0” as a development of conventional single minute exchange of die (SMED) to avoid defect occurrence during production and improve sustainability, besides reducing setup time.

The method builds upon an extensive literature review and in-depth explorative research in SMED and zero defect manufacturing (ZDM). SMED 4.0 incorporates an evolutionary stage that employs predict-prevent strategies using Industry 4.0 technologies including the Internet of Things (IoT) and machine learning (ML) algorithms.

It presents the applicability of the proposed approach in (1) identifying the triple bottom line (TBL) criteria, which are affected by defects; (2) predicting the time of defect occurrence if any; (3) preventing defective products by performing online setting on machines during production as needed; (4) maintaining the desired quality of the product during the production and (5) improving TBL sustainability in manufacturing processes.

The extended view of SMED 4.0 in this research, as well as its analytical approach, helps practitioners develop their SMED approaches in a more holistic way. The practical application of SMED 4.0 is illustrated by implementing it in a real-life manufacturing case.

This study aims to provide the best estimate of a stock's next day's closing price for a given day with the help of the hidden Markov model–Gaussian mixture model (HMM-GMM). The results were compared with Hassan and Nath’s (2005) study using HMM and artificial neural network (ANN).

The study adopted an initialization approach wherein the hidden states of the HMM are modelled as GMM using two different approaches. Training of the HMM-GMM model is carried out using two methods. The prediction was performed by taking the closest closing price (having a log-likelihood within the tolerance range) to that of the present one as the closing price for the next day. Mean absolute percentage error (MAPE) has been used to compare the proposed GMM-HMM model against the models of the research study (Hassan and Nath, 2005).

Comparing this study with Hassan and Nath (2005) reveals that the proposed model outperformed in 66 out of the 72 different test cases. The results affirm that the model can be used for more accurate time series prediction. Further, compared with the results of the ANN model from Hassan's study, the proposed HMM model outperformed 24 of the 36 test cases.

The study introduced a novel initialization and two training/prediction approaches for the HMM-GMM model. It is to be noted that the study has introduced a GMM-HMM-based closing price estimator for stock price prediction. The proposed method of forecasting the stock prices using GMM-HMM is explainable and has a solid statistical foundation.

This paper aims to examine the association between environmental disclosure and waste performance.

This study is based on a sample of S&P 500 firms over a nine-year period from 2010 to 2018. The pooled ordinary least squares (OLS), logistic, propensity score matching (PSM) and instrumental variable-generalized method of moments regressions analyses have been used to examine the data.

The findings show a significant positive relationship between waste performance and environmental disclosure, suggesting that firms with superior waste performance tend to disclose more environmental information. Further, the authors distinguish between “hard” and “soft” environmental disclosures and find that the effect of waste performance is consistently positive and significant for each type. The observed positive and significant association of waste performance with environmental disclosure remains unchanged, regardless of the industry affiliation of firms, although firms from industries that are less environmentally sensitive provide a slightly higher level of environmental disclosure. The authors also explore possible channels that may explain the association between waste performance and environmental disclosure and find that litigation risk and cash holdings positively moderate the association. The finding remains robust to a number of alternative estimation approaches.

Overall, the authors present important evidence that waste performance is an important indicator of environmental disclosure. The findings are useful for corporations and stakeholders and have important implications around the globe as the authors continue to grapple with the ongoing issue of waste.